Prof Ravinesh Deo

Prof Ravinesh Deo
NameProf Ravinesh Deo
Email Addressravinesh.deo@unisq.edu.au
Job TitleProfessor (Mathematics)
QualificationsBSc South Pacific, GCertTT&L USQ, MSc(Hons) Canterbury, PhD Adelaide
DepartmentSchool of Mathematics, Physics and Computing
AffiliationsInstitute for Advanced Engineering and Space Sciences
Centre for Applied Climate Sciences
Centre for Health Research
ORCIDhttps://orcid.org/0000-0002-2290-6749
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Biography

Prof. Ravinesh Deo's research interests include artificial intelligence and its applications in health, energy, wireless communication (national intelligence & defence), environment and engineering. His primary field of research (FOR) code is 4611 (Machine Learning), 4602 (Artificial Intelligence) and 4601 (Applied Computing). He is ranked in the Top 1% of researchers by Clarivate Analytics/Web of Science (2021) and in the Top 2% of World Scientists by Stanford University, USA (2021-2023).

Prof Deo completed senior school education at Labasa College (Fiji) and received a PhD in Signal Processing from The University of Adelaide, Australia. Currently, he leads UniSQ's Advanced Data Analytics Research Laboratory (57+ researchers and graduate students), having supervised more than 40 PhD and Master's degrees with more than fifteen students receiving Doctoral Excellence Awards, Masters Excellence Awards, or Thesis Distinction Awards. He has published over 300 scholarly papers, including 180 papers (89.6%) in Q1 journals as well as co-authored research with over 425 scientists worldwide, earning him a Field-Weighted Citation Index of 3.0+ and a productive international research program publishing with 190+ institutions across five continents (North America, Europe, Africa, Asia, Australia; SciVal, 2024).

Aside from grants from the Spanish National Projects, Iberdrola and the European Union Horizon 20, he received grants from the Department of Defence, Office of National Intelligence and the Queensland government and six research fellowships (Advance Queensland Smithsonian Fellowship, Young Scientist Exchange Award, JSPS Fellowship, Australia-India Strategic Fellowship, Endeavour Fellowship). These have enriched his research in artificial intelligence and its applications.

Prof Deo is an Editor for IEEE Access, Engineering Applications of Artificial Intelligence, and Stochastic Environmental Research and Risk Assessment. He has won the Outstanding School Researcher Award for 2023/2022, the Excellence in Research Award for 2021, and the Ronel Erwee Memorial Award for Excellence in Postgraduate Research Supervision, along with publication excellence and Elsevier's Highly Cited Paper Award. He mentors early- and mid-career researchers at UniSQ's Advanced Data Analytics Research Lab in renewable energy, artificial intelligence, defence and engineering fields.

Employment

PositionOrganisationFromTo
Professor of Mathematics & Researcher in Artificial IntelligenceUniversity of Southern Queensland20212023
Associate Professor of Mathematics & Researcher in Artificial IntelligenceUniversity of Southern Queensland20202020
Senior Lecturer in MathematicsUniversity of Southern Queensland20162019
Lecturer in MathematicsUniversity of Southern Queensland20102015
Principal Research ScientistQueensland Government20092010
Postdoctoral Research FellowThe University of Southern Queensland20062009
Associate Lecturer in PhysicsThe University of the South Pacific Fiji20052006

Expertise

Professor Deo has received competitive research grants in the areas of Health, Engineering, Renewable Energy, Communication, Defence and National Intelligence, Environmental and Engineering. Among his key areas of expertise are Artificial Intelligence and Machine Learning, Knowledge and Data Engineering, Deep Learning, Evolutionary Computational Intelligence, and Optimisation Methods. Professor Deo's extensive research in various fields has greatly contributed to advancements in several areas. His work in health has led to improved diagnosis and treatment methods, while his research in engineering and renewable energy has contributed to sustainable and innovative solutions. Furthermore, his expertise in communication and defence has helped advance technological advancements in these areas. Thus, Professor Deo's research has had a significant impact in fields such as health, engineering, renewable energy, communication, defence, and national intelligence.

Teaching

Professor Deo is a dedicated supervisor of over 15 PhDs (Principal & Associate, Master of Research and Master of Science (Principal & Associate Supervisor). He also teaches engineering mathematics, research methods and thesis development in MSC 6001 & MSC 6002 courses.

Fields of Research

  • 460102. Applications in health
  • 460104. Applications in physical sciences
  • 460201. Artificial life and complex adaptive systems
  • 460203. Evolutionary computation
  • 460204. Fuzzy computation
  • 460207. Modelling and simulation
  • 461101. Adversarial machine learning
  • 461103. Deep learning
  • 461104. Neural networks

Professional Membership

Professional MembershipYear
IEEE - Elevated to a Senior Member
National Tertiary Education Union
Elsevier Editorial Board
Springer Editorial Board
BSc
South Pacific
1998
GCertTT&L
USQ
2011
MSc(Hons)
Canterbury
2002
PhD
Adelaide
2005

Supervision Interests

Artificial Intelligence and Machine Learning Applications for Aviation and Energy Industries

Current Supervisions

Research TitleSupervisor TypeLevel of StudyCommenced
Cotutelle PhD Program (International Partnership, UniSQ-Universidad de Alcala) - César PELÁEZ RODRÍGUEZPrincipal SupervisorDoctoral2023
Cotutelle PhD Program (International Partnership, UniSQ-Federal University of São Paulo) - Andréia Seixas LealPrincipal SupervisorDoctoral2024
A Deep Learning-Based Framework for Depression Detection Using EEG and MRI DataAssociate SupervisorMasters2025
Artificial Intelligence Forecast Models of Air Quality in Real-Time Predictive SystemsPrincipal SupervisorDoctoral2025
Identification and characterization of novel resistance genes for wheat stripe rust from Watkins¿ landrace collectionAssociate SupervisorDoctoral2024
Application of Artificial Intelligence Techniques for Neurodevelopmental Disorders in Children Using Physiological SignalsPrincipal SupervisorDoctoral2024
AI-enabled Early Detection Tools to Identify Student's Academic Progress and Decisions to Initiate Early Intervention - a review of higher education settingsPrincipal SupervisorDoctoral2024
Machine learning in predictive maintenance with IoT sensors data towards Intelligent Systems in Aviation 4.0 IndustryPrincipal SupervisorDoctoral2024
Automated language detection model using artificial intelligence techniques with EEG signalsPrincipal SupervisorDoctoral2023
Explainable-AI driven deep learning modelling of climate change characteristicsAssociate SupervisorMasters2023
Joint Assimilation of RS Satellite derived Leaf area index and soil moisture into DSSAT-CSM for cotton growth monitoring and yield predictionAssociate SupervisorDoctoral2023
Investigate the methods for fast incremental learning of machine learning models for misuse and anomaly-based intrusion detection in the cyber-attack domain.Associate SupervisorDoctoral2023
Epileptic Seizure Prediction with Heart Rate Variability and ECG DatasetsPrincipal SupervisorDoctoral2022
An Efficient Automated Tool to Characterise Asthma using cough sound signalsPrincipal SupervisorDoctoral2022
Automated accurate retinal health screening systemPrincipal SupervisorDoctoral2022
Deep learning assisted ultrasensitive SiC sensors for physical monitoringAssociate SupervisorDoctoral2022
Predicting Sea Level Rise in Australia with Oceanographic Data-Driven Insights, Artificial Intelligence, and Deep Learning AlgorithmsAssociate SupervisorDoctoral2022
International Students Online Learning Engagement in Australian Higher Education: A Case Study of South Asian International StudentsAssociate SupervisorMasters2022
Gaps in, and limitations of existing climate adaptation policies in Fiji and barriers to further changesPrincipal SupervisorMasters2022
Predicting erythemally-effective solar ultraviolet irradiation under attenuation factors and cloudy variation using explainable AI (XAI) and physical modelling methodPrincipal SupervisorDoctoral2022
AI-enabled enrolment/application process through an integrated platformAssociate SupervisorDoctoral2021
Hybrid Deep Learning Artificial Intelligent Models for wind speed forecasting in wind-rich regions in AustraliaAssociate SupervisorDoctoral2020
Sustainable energy futures: Modelling energy demand using global climate models and developing interpretable models with Bayesian approachesPrincipal SupervisorDoctoral2020
VEGETATION DYNAMICS AND CLIMATE CHANGE IMPACTS IN ZAMBIAS SAVANNAS: ANALYSIS USING GEOSPATIAL TECHNIQUES AND CLIMATE MODELLING APPROACHESAssociate SupervisorDoctoral2019

Completed Supervisions

Research TitleSupervisor TypeLevel of StudyCompleted
Artificial Intelligence Methods for Prediction of Atmospheric Visibility and Air Quality to Support Aviation and Health SectorsPrincipal SupervisorMasters2024
Advancing Stochastic Wind Speed Forecasting Methods with Novel Hybrid Deep Learning TechniquesPrincipal SupervisorDoctoral2024
Artificial Intelligence and Copula-Probabilistic Models for Early Flood Warning and Community Risk Management: Case Studies in Fiji IslandsPrincipal SupervisorMasters2024
Applied Deep Learning for Artificial Intelligence-enabled Wireless CommunicationPrincipal SupervisorDoctoral2024
Solar Ultraviolet Radiation Predictions Under Cloud Cover Effects with Artificial Intelligence ApproachesPrincipal SupervisorDoctoral2023
Artificial Intelligence informed Simulation of Dissolved Inorganic Nitrogen from Ungauged Catchments to the Great Barrier ReefPrincipal SupervisorDoctoral2023
Evaporation and Soil Moisture Prediction with Artificial Intelligence and Deep Learning MethodsPrincipal SupervisorDoctoral2023
Coloured Image Classification with Quantum Machine Learning Algorithms for Intelligent Transportation SystemsAssociate SupervisorDoctoral2023
USING MACHINE LEARNING BASED EMULATORS FOR SENSITIVITY ANALYSIS OF PROCESS-DRIVEN BIOPHYSICAL MODELSAssociate SupervisorDoctoral2022
ARTIFICIAL INTELLIGENCE AND CLEAN AIR:DEVELOPMENT OF NOVEL ALGORITHMS WITH MACHINE LEARNING AND DEEP LEARNINGPrincipal SupervisorDoctoral2022
Development of Deep Learning Predictive Models for Hydrological PredictionsPrincipal SupervisorDoctoral2022
NUCLEAR RIBOSOMAL DNA SECONDARY STRUCTURES AND STATISTICAL APPROACH FOR THE PHYLOGENY OF AMPELOMYCESAssociate SupervisorDoctoral2022
An integrated systems model for sustainable agricultural development under changing climate: A case study in a coffee production system in VietnamAssociate SupervisorDoctoral2021
Development of flood risk monitoring and forecasting system with artificial intelligence predictive models for community risk management in FijiPrincipal SupervisorMasters2021
DEVELOPING ARTIFICIAL INTELLIGENCE MODELS FOR CLASSIFICATION OF BRAIN DISORDER DISEASES BASED ON STATISTICAL TECHNIQUESAssociate SupervisorDoctoral2021
DEVELOPMENT AND EVALUATION OF DATA-DRIVEN MODELSFOR ELECTRICITY DEMAND FORECASTING IN QUEENSLAND,AUSTRALIAPrincipal SupervisorMasters2020
Development of deep learning predictive models for short-term solar radiation forecasting: Case study in VietnamPrincipal SupervisorMasters2020
Development of data intelligent models for electricity demand forecasting: Case studies in the state of Queensland, AustraliaPrincipal SupervisorDoctoral2020
Enhanced deep learning predictive modelling approaches for pain intensity recognition from facial expression video imagesAssociate SupervisorDoctoral2020
Forecasting seasonal rainfall with copula modelling approach for agricultural stations in Papua New GuineaPrincipal SupervisorMasters2019
Predictive modelling of global solar radiation with artificial intelligence approaches using MODIS satellites and atmospheric reanalysis data for AustraliaPrincipal SupervisorDoctoral2019
Probabilistic and artificial intelligence modelling of drought and agricultural crop yield in PakistanPrincipal SupervisorDoctoral2019
Copula-based statistical modelling of synoptic-scale climate indices for quantifying and managing agricultural risks in AustraliaPrincipal SupervisorDoctoral2018
Streamflow and soil moisture forecasting with hybrid data intelligent machine learning approaches: Case studies in the Australian Murray-Darling BasinPrincipal SupervisorDoctoral2018
Development of statistical and geospatial-based framework for drought-risk assessmentPrincipal SupervisorDoctoral2018
An wavelet-coupled artificial neural network-bootstrap model for environmental applications (Solar energy forecasting)Principal SupervisorMasters2018
Project titleDetailsYear
Department of DefenceSoftware Defined Radios: Over-the-air Trainable Wave-forms. $72,452. Prof R. Deo, Christopher Davey & Defence Lead. 2021-2024. 2024
Asia Pacific Network for Global ChangeDeveloping a new integrated physical-statistical-financial approach for regional flood risk reduction under climate change. $129,000. Dr T. Nguyen, Prof R. Deo, Prof. S. Mushtaq. 2023-2024.2023
CSIRO EnvironmentForecasting Water Quality in Rivers using Machine Learning. $26,700. Prof R. Deo, Dr Klaus Joehnk & Leyde Briceno Medina. 2023-2025. 2023
Office of National Intelligence, Australian GovernmentInternet of Space Things - Power-efficient Coded-Modulation Schemes for Low Earth Orbit (LEO) Satellite Communication. $349,962. Dr E. Sharma & Prof R. Deo. 2022-2024.2022
Cogninet AI Industry Research Program Artificial Intelligence for Health & Education Technologies: Asthma & Neurological Disorder Prediction. $256,000. Prof R Acharya, Prof R Deo, Prof J Soar, Prof P Barua. 2022-2025. 2022
Department of Defence$30,000. Artificial Intelligence for Decision-Making (AI4DM). (Prof Ravinesh Deo, & Christopher Davey). 2022. 2022
CSIRO Data 61Quantum Computing and Quantum Machine Learning. $26,700. Prof R Deo, Dr Shahab Abdulla, Dr Farina Riyaz. 2021–2023.2021
Senetas CorporationAI & ML for Signal Processing - Australian Postgraduate Research Internships. $26,000. Prof R Deo, & Sagthitharan Karalasingham (PhD Intern). 2021. 2021
CS EnergyBias Correction in Weather Models for Solar Generation - Australian Postgraduate Research Internships. $26,000. Prof R Deo & Dr Abul Masrur (PhD Intern). 2021
Department of DefenceAI-enabled Communications. $90,000. Prof R Deo, Christopher Davey (PhD researcher) & Defence Lead.2021
Australia India Strategic Research FundEnhancing climate change adaptation processes for farmers and agribusiness - Australia India Strategic Research Fund. $989,979. Prof R Stone, Prof S. Mushtaq; T. Marcussen; Dr J. Kath; Dr L. Kouadio; Dr C. Pudmenzky; Prof R Deo. 2020 – 2023. Round 12 with Tamil Nadu Agricultural University, India. 2020
Department of DefenceEfficient Algorithms for AI-enabled Communication- Australian Postgraduate Research Internships. $26,000. Prof R Deo, Dr E Sharma (PhD researcher) & Defence Lead. 2020
SOIL CRC. High Performance SoilsNovel sensor technology to measure and map soil nutrients, water and hydraulic characteristics- SOIL CRC. High Performance Soils. $599,938 (Total = $1,701,494). Dr C. Lobsey, J. Albion, Prof J. Bennett, Prof Hedley C, Prof Roudier P, Prof R Deo., Y Zhu, D., D West, L Bella, M. Sefton, R Mila.2019
Australian Bureau of StatisticsBig Data for Multipurpose Surveys - Australian Postgraduate Research Internships. $26,000. Prof R Deo & Mohanad Al-Musaylh. 2019
Queensland GovernmentMachine Learning Automation of Whole of Government Transaction Automation - Australian Postgraduate Research Internships. $21,500. Prof R Deo & Dr Andrei 2019-2022. 2019
Chinese Academy of SciencesIntegration of Water Security in Northeast Area. $117,500. Prof Ravinesh Deo, Dr Abul Masrur, Prof Feng Qi. 2019
Advance Queensland USA Smithsonian Research FellowshipAttributing land use/land-cover change influence on hydrological-ecosystem interactions with artificial intelligence. $16,250. Prof R Deo & Dr J. Hall (STRI, Panama). 2017
DateNameAwarding organisationUnderpinning research
2023Associate EditorEngineering Applications of Artificial Intelligence
2021IEEE AccessThe Institute of Electrical and Electronics Engineers, USA
2018Recipient of: Advance Queensland Smithsonian Research FellowshipQueensland Government
2017Recipient of: JSPS Fellowship (Japan Society for Promotion of Science International Invitational Research Fellowship)Japan Society for Promotion of Science/The University of Tokyo/Kyoto University/Kyushu University
2015Endeavour Executive FellowshipAustralian Government
2021Highly Cited Researcher (Top 1%)Clarivate Analytics Web of Science
2021Top 2% of World ScientistStanford University, USA

Comparison of machine learning methods emulating process driven crop models

Johnston, David B., Pembleton, Keith G., Huth, Neil I. and Deo, Ravinesh C.. 2023. "Comparison of machine learning methods emulating process driven crop models ." Environmental Modelling and Software. 162. https://doi.org/10.1016/j.envsoft.2023.105634

Accurate Image Multi-Class Classification Neural Network Model with Quantum Entanglement Approach

Riaz, Farina, Abdulla, Shahab, Suzuki, Hajime, Ganguly, Srinjoy, Deo, Ravinesh C. and Hopkins, Susan. 2023. "Accurate Image Multi-Class Classification Neural Network Model with Quantum Entanglement Approach." Sensors. 23 (5), pp. 1-11. https://doi.org/10.3390/s23052753

Near real-time wind speed forecast model with bidirectional LSTM networks

Joseph, Lionel P., Deo, Ravinesh C., Prasad, Ramendra, Salcedo-Sanz, Sancho, Raj, Nawin and Soar, Jeffrey. 2023. "Near real-time wind speed forecast model with bidirectional LSTM networks." Renewable Energy. 204, pp. 39-58. https://doi.org/10.1016/j.renene.2022.12.123

Cloud cover bias correction in numerical weather models for solar energy monitoring and forecasting systems with kernel ridge regression

Deo, Ravinesh C., Ahmed, A.A. Masrur, Casillas-Perez, David, Pourmousavi, S. Ali, Segal, Gary, Yu, Yanshan and Salcedo-sanz, Sancho. 2023. "Cloud cover bias correction in numerical weather models for solar energy monitoring and forecasting systems with kernel ridge regression." Renewable Energy. 203, pp. 113-130. https://doi.org/10.1016/j.renene.2022.12.048

The Great 2011 Thailand flood disaster revisited: Could it have been mitigated by different dam operations based on better weather forecasts?

Loc, Ho Huu, Emadzadeh, Adel, Park, Edward, Nontikansak, Piyanuch and Deo, Ravinesh C.. 2023. "The Great 2011 Thailand flood disaster revisited: Could it have been mitigated by different dam operations based on better weather forecasts? " Environmental Research. 216 (Part 2). https://doi.org/10.1016/j.envres.2022.114493

A novel approach based on integration of convolutional neural networks and echo state network for daily electricity demand prediction

Ghimire, Sujan, Nguyen-Huy, Thong, AL-Musaylh, Mohanad S., Deo, Ravinesh, Casillas-Perez, David and Salcedo-sanz, Sancho. 2023. "A novel approach based on integration of convolutional neural networks and echo state network for daily electricity demand prediction." Energy. 275, p. 127430. https://doi.org/10.1016/j.energy.2023.127430

Downscaling Surface Albedo to Higher Spatial Resolutions With an Image Super-Resolution Approach and PROBA-V Satellite Images

Deo, Ravinesh C., Karalasingham, Sagthitharan, Casillas-Perez, David, Raj, Narwin and Salcedo-sanz, Sancho. 2023. "Downscaling Surface Albedo to Higher Spatial Resolutions With an Image Super-Resolution Approach and PROBA-V Satellite Images." IEEE Access. 11, pp. 5558-5577. https://doi.org/10.1109/ACCESS.2023.3236253

Developing a novel hybrid method based on dispersion entropy and adaptive boosting algorithm for human activity recognition

Diykh, Mohammed, Abdulla, Shahab, Deo, Ravinesh C, Siuly, Siuly and Ali, Mumtaz. 2023. "Developing a novel hybrid method based on dispersion entropy and adaptive boosting algorithm for human activity recognition." Computer Methods and Programs in Biomedicine. 229. https://doi.org/10.1016/j.cmpb.2022.107305

Deep Multi-Stage Reference Evapotranspiration Forecasting Model: Multivariate Empirical Mode Decomposition Integrated With the Boruta-Random Forest Algorithm

Jayasinghe, W. J. M. Lakmini Prarthana, Deo, Ravinesh C., Ghahramani, Afshin, Ghimire, Sujan and Raj, Nawin. 2021. "Deep Multi-Stage Reference Evapotranspiration Forecasting Model: Multivariate Empirical Mode Decomposition Integrated With the Boruta-Random Forest Algorithm." IEEE Access. 9, pp. 166695-166708. https://doi.org/10.1109/ACCESS.2021.3135362

Designing Deep-based Learning Flood Forecast Model with ConvLSTM Hybrid Algorithm

Moishin, Mohammed, Deo, Ravinesh C., Prasad, Ramendra, Raj, Nawin and Abdulla, Shahab. 2021. "Designing Deep-based Learning Flood Forecast Model with ConvLSTM Hybrid Algorithm." IEEE Access. 9, pp. 50982-50993. https://doi.org/10.1109/ACCESS.2021.3065939

A hierarchical classification/regression algorithm for improving extreme wind speed events prediction

Pelaez-Rodriguez, C., Perez-Aracil, J., Fister, D, Prieto-Godino, L., Deo, R.C. and Salcedo-sanz, S.. 2022. "A hierarchical classification/regression algorithm for improving extreme wind speed events prediction." Renewable Energy. 201 (Part 2), pp. 157-178. https://doi.org/10.1016/j.renene.2022.11.042

Pattern recognition describing spatio-temporal drivers of catchment classification for water quality

O'Sullivan, Cherie M., Ghahramani, Afshin, Deo, Ravinesh C. and Pembleton, Keith G.. 2023. "Pattern recognition describing spatio-temporal drivers of catchment classification for water quality." Science of the Total Environment. 861, pp. 1-42. https://doi.org/10.1016/j.scitotenv.2022.160240

The Playground Shade Index: A New Design Metric for Measuring Shade and Seasonal Ultraviolet Protection Characteristics of Parks and Playgrounds

Downs, Nathan, Raj, Nawin, Vanos, Jennifer, Parisi, Alfio, Butler, Harry, Deo, Ravinesh, Igoe, Damien, Dexter, Benjamin, Beckman-Downs, Melanie, Turner, Joanna and Dekeyser, Stijn. 2023. "The Playground Shade Index: A New Design Metric for Measuring Shade and Seasonal Ultraviolet Protection Characteristics of Parks and Playgrounds." Photochemistry and Photobiology. 99 (4), pp. 1193-1207. https://doi.org/10.1111/php.13745

Using Sequence-to-Sequence Models for Carrier Frequency Offset Estimation of Short Messages and Chaotic Maps

Davey, Christopher P., Shakeel, Ismail, Deo, Ravinesh C., Salcedo-sanz, Sancho and Soar, Jeffrey. 2022. "Using Sequence-to-Sequence Models for Carrier Frequency Offset Estimation of Short Messages and Chaotic Maps." IEEE Access. 10, pp. 119814 - 119825. https://doi.org/10.1109/ACCESS.2022.3221762

Modelling and Real-time Optimisation of Air Quality Predictions for Australia through Artificial Intelligence Algorithm

Sharma, Ekta, Deo, Ravinesh C., Prasad, Ramendra and Parisi, Alfio V.. 2019. "Modelling and Real-time Optimisation of Air Quality Predictions for Australia through Artificial Intelligence Algorithm." AMSI Optimise 2019. Perth, Australia 17 - 21 Jun 2019 Perth, Australia.

Hybrid Convolutional Neural Network-Multilayer Perceptron Model for Solar Radiation Prediction

Ghimire, Sujan, Nguyen-Huy, Thong, Prasad, Ramendra, Deo, Ravinesh C., Casillas-Perez, David, Salcedo-sanz, Sancho and Bhandari, Binayak. 2023. "Hybrid Convolutional Neural Network-Multilayer Perceptron Model for Solar Radiation Prediction." Cognitive Computation. 15 (2), pp. 645-671. https://doi.org/10.1007/s12559-022-10070-y

Student Performance Predictions for Advanced Engineering Mathematics Course With New Multivariate Copula Models

Nguyen-Huy, Thong, Deo, Ravinesh C., Khan, Shahjahan, Devi, Aruna, Adeyinka, Adewuyi Ayodele, Apan, Armando A. and Yaseen, Zaher Mundher. 2022. "Student Performance Predictions for Advanced Engineering Mathematics Course With New Multivariate Copula Models." IEEE Access. 10, pp. 45112 -45136. https://doi.org/10.1109/ACCESS.2022.3168322

Rapid assessment of mine rehabilitation areas with airborne LiDAR and deep learning: bauxite strip mining in Queensland, Australia

Murray, Xavier, Apan, Armando, Deo, Ravinesh and Maraseni, Tek. 2022. "Rapid assessment of mine rehabilitation areas with airborne LiDAR and deep learning: bauxite strip mining in Queensland, Australia." Geocarto International. 37 (26), pp. 11223-11252. https://doi.org/10.1080/10106049.2022.2048902

Multi-strategy Slime Mould Algorithm for hydropower multi-reservoir systems optimization

Ahmadianfar, Iman, Noori, Ramzia Majeed, Togun, Hussein, Falah, Mayadah W., Homod, Raad Z., Fu, Minglei, Halder, Bijay, Deo, Ravinesh and Yaseen, Zaher Mundher. 2022. "Multi-strategy Slime Mould Algorithm for hydropower multi-reservoir systems optimization." Knowledge-Based Systems. 250, pp. 1-18. https://doi.org/10.1016/j.knosys.2022.109048

Suspended sediment load modeling using advanced hybrid rotation forest based elastic network approach

Khosravi, Khabat, Golkarian, Ali, Melesse, Assefa M. and Deo, Ravinesh C.. 2022. "Suspended sediment load modeling using advanced hybrid rotation forest based elastic network approach." Journal of Hydrology. 610, pp. 1-14. https://doi.org/10.1016/j.jhydrol.2022.127963

Delineating the Crop-Land Dynamic due to Extreme Environment Using Landsat Datasets: A Case Study

Halder, Bijay, Bandyopadhyay, Jatisankar, Afan, Haitham Abdulmohsin, Naser, Maryam H., Abed, Salwan Ali, Khedher, Khaled Mohamed, Falih, Khaldoon T., Deo, Ravinesh, Scholz, Miklas and Yaseen, Zaher Mundher. 2022. "Delineating the Crop-Land Dynamic due to Extreme Environment Using Landsat Datasets: A Case Study." Agronomy. 12 (6), pp. 1-23. https://doi.org/10.3390/agronomy12061268

Coupled online sequential extreme learning machine model with ant colony optimization algorithm for wheat yield prediction

Ali, Mumtaz, Deo, Ravinesh C., Xiang, Yong, Prasad, Ramendra, Li, Jianxin, Farooque, Aitazaz and Yaseen, Zaher Mundher. 2022. "Coupled online sequential extreme learning machine model with ant colony optimization algorithm for wheat yield prediction." Scientific Reports. 12 (1), pp. 1-23. https://doi.org/10.1038/s41598-022-09482-5

Forecasting solar photosynthetic photon flux density under cloud cover effects: novel predictive model using convolutional neural network integrated with long short-term memory network

Deo, Ravinesh C., Grant, Richard H., Webb, Ann, Ghimire, Sujan, Igoe, Damien P., Downs, Nathan J., Al-Musaylh, Mohanad S., Parisi, Alfio V. and Soar, Jeffrey. 2022. "Forecasting solar photosynthetic photon flux density under cloud cover effects: novel predictive model using convolutional neural network integrated with long short-term memory network." Stochastic Environmental Research and Risk Assessment. 36, p. 3183–3220. https://doi.org/10.1007/s00477-022-02188-0

Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise Deep Residual model for short-term multi-step solar radiation prediction

Ghimire, Sujan, Deo, Ravinesh C, Casillas-Perez, David and Salcedo-sanz, Sancho. 2022. "Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise Deep Residual model for short-term multi-step solar radiation prediction." Renewable Energy. 190, pp. 408-424. https://doi.org/10.1016/j.renene.2022.03.120

Efficient daily solar radiation prediction with deep learning 4-phase convolutional neural network, dual stage stacked regression and support vector machine CNN-REGST hybrid model

Ghimire, Sujan, Nguyen-Huy, Thong, Deo, Ravinesh C., Casillas-Perez, David and Salcedo-sanz, Sancho. 2022. "Efficient daily solar radiation prediction with deep learning 4-phase convolutional neural network, dual stage stacked regression and support vector machine CNN-REGST hybrid model." Sustainable Materials and Technologies. 32, pp. 1-24. https://doi.org/10.1016/j.susmat.2022.e00429

Hybrid deep CNN-SVR algorithm for solar radiation prediction problems in Queensland, Australia

Ghimire, Sujan, Bhandari, Binayak, Casillas-Perez, David, Deo, Ravinesh C. and Salcedo-sanz, Sancho. 2022. "Hybrid deep CNN-SVR algorithm for solar radiation prediction problems in Queensland, Australia." Engineering Applications of Artificial Intelligence. 112, pp. 1-26. https://doi.org/10.1016/j.engappai.2022.104860

Boosting solar radiation predictions with global climate models, observational predictors and hybrid deep-machine learning algorithms

Ghimire, Sujan, Deo, Ravinesh C., Casillas-Perez, David and Salcedo-sanz, Sancho. 2022. "Boosting solar radiation predictions with global climate models, observational predictors and hybrid deep-machine learning algorithms." Applied Energy. 316, pp. 1-25. https://doi.org/10.1016/j.apenergy.2022.119063

Machine learning regression and classification methods for fog events prediction

Castillo-Boton, C., Casillas-Perez, D., Casanova-Mateo, C., Ghimire, S., Cerro-Prada, E., Gutierrez, P. A., Deo, R. C. and Salcedo-sanz, S.. 2022. "Machine learning regression and classification methods for fog events prediction." Atmospheric Research. 272, pp. 1-23. https://doi.org/10.1016/j.atmosres.2022.106157

Quantum Artificial Intelligence Predictions Enhancement by Improving Signal Processing

Riaz, Farina, Abdulla, Shahab, Ni, Wei, Radfar, Mohsen, Deo, Ravinesh and Hopkins, Susan. 2022. "Quantum Artificial Intelligence Predictions Enhancement by Improving Signal Processing." Quantum Australia Conference 2022. Online 23 - 25 Feb 2022 Toowoomba, Australia. https://doi.org/10.13140/RG.2.2.34754.66245

Deep learning CNN-LSTM-MLP hybrid fusion model for feature optimizations and daily solar radiation prediction

Ghimire, Sujan, Deo, Ravinesh C., Casillas-Perez, David, Salcedo-sanz, Sancho, Sharma, Ekta and Ali, Mumtaz. 2022. "Deep learning CNN-LSTM-MLP hybrid fusion model for feature optimizations and daily solar radiation prediction." Measurement. 202, pp. 1-22. https://doi.org/10.1016/j.measurement.2022.111759

Basin management inspiration from impacts of alternating dry and wet conditions on water production and carbon uptake in Murray-Darling Basin

Lu, Zhixiang, Feng, Qi, Wei, Yongping, Zhao, Yan, Deo, Ravinesh C., Xie, Jiali, Zhou, Sha, Zhu, Meng and Xu, Min. 2022. "Basin management inspiration from impacts of alternating dry and wet conditions on water production and carbon uptake in Murray-Darling Basin." Science of the Total Environment. 851 (Part 2), pp. 1-8. https://doi.org/10.1016/j.scitotenv.2022.158359

Introductory Engineering Mathematics Students’ Weighted Score Predictions Utilising a Novel Multivariate Adaptive Regression Spline Model

Ahmed, Abul Abrar Masrur, Deo, Ravinesh C., Ghimire, Sujan, Downs, Nathan J., Devi, Aruna, Barua, Prabal D. and Yaseen, Zaher M.. 2022. "Introductory Engineering Mathematics Students’ Weighted Score Predictions Utilising a Novel Multivariate Adaptive Regression Spline Model." Sustainability. 14 (17), pp. 1-27. https://doi.org/10.3390/su141711070

Kernel Ridge Regression Hybrid Method for Wheat Yield Prediction with Satellite-Derived Predictors

Ahmed, A. A. Masrur, Sharma, Ekta, Jui, S. Janifer Jabin, Deo, Ravinesh C., Nguyen-Huy, Thong and Ali, Mumtaz. 2022. "Kernel Ridge Regression Hybrid Method for Wheat Yield Prediction with Satellite-Derived Predictors." Remote Sensing. 14 (5), pp. 1-24. https://doi.org/10.3390/rs14051136

Cloud Affected Solar UV Predictions with Three-Phase Wavelet Hybrid Convolutional Long Short-Term Memory Network Multi-Step Forecast System

Prasad, Salvin S., Deo, Ravinesh C., Downs, Nathan, Igoe, Damien, Parisi, Alfio V. and Soar, Jeffrey. 2022. "Cloud Affected Solar UV Predictions with Three-Phase Wavelet Hybrid Convolutional Long Short-Term Memory Network Multi-Step Forecast System." IEEE Access. 10, pp. 24704-24720. https://doi.org/10.1109/ACCESS.2022.3153475

Integrative artificial intelligence models for Australian coastal sediment lead prediction: An investigation of in-situ measurements and meteorological parameters effects

Bhagat, Suraj Kumar, Tiyasha, Tiyasha, Kumar, Adarsh, Malik, Tabarak, Jawad, Ali H., Khedher, Khaled Mohamed, Deo, Ravinesh C. and Yaseen, Zaher Mundher. 2022. "Integrative artificial intelligence models for Australian coastal sediment lead prediction: An investigation of in-situ measurements and meteorological parameters effects." Journal of Environmental Management. 309, pp. 1-16. https://doi.org/10.1016/j.jenvman.2022.114711

An Eigenvalues-Based Covariance Matrix Bootstrap Model Integrated With Support Vector Machines for Multichannel EEG Signals Analysis

Al-Hadeethi, Hanan, Abdulla, Shahab, Diykh, Mohammed, Deo, Ravinesh C. and Green, Jonathan H.. 2022. "An Eigenvalues-Based Covariance Matrix Bootstrap Model Integrated With Support Vector Machines for Multichannel EEG Signals Analysis." Frontiers in Neuroinformatics. 15, pp. 1-15. https://doi.org/10.3389/fninf.2021.808339

Stacked LSTM Sequence-to-Sequence Autoencoder with Feature Selection for Daily Solar Radiation Prediction: A Review and New Modeling Results

Ghimire, Sujan, Deo, Ravinesh C., Wang, Hua, Al-Musaylh, Mohanad S., Casillas-Perez, David and Salcedo-sanz, Sancho. 2022. "Stacked LSTM Sequence-to-Sequence Autoencoder with Feature Selection for Daily Solar Radiation Prediction: A Review and New Modeling Results." Energies. 15 (3), pp. 1-39. https://doi.org/10.3390/en15031061

Texture analysis based graph approach for automatic detection of neonatal seizure from multi-channel EEG signals

Diykh, Mohammed, Miften, Firas Sabar, Abdulla, Shahab, Deo, Ravinesh C., Siuly, Siuly, Green, Jonathan H. and Oudah, Atheer Y.. 2022. "Texture analysis based graph approach for automatic detection of neonatal seizure from multi-channel EEG signals." Measurement. 190 (110731), pp. 1-13. https://doi.org/10.1016/j.measurement.2022.110731

Domino effect of climate change over two millennia in ancient China’s Hexi Corridor

Feng, Qi, Yan, Linshan, Deo, Ravinesh C., AghaKouchak, Amir, Adamowski, Jan F., Stone, Roger, Yin, Zhenliang, Liu, Wei, Si, Jianhua, Wen, Xiaohu, Zhu, Meng and Cao, Shixiong. 2019. "Domino effect of climate change over two millennia in ancient China’s Hexi Corridor." Nature Sustainability. 2, pp. 957-961. https://doi.org/10.1038/s41893-019-0397-9

Bat algorithm for dam–reservoir operation

Ethteram, Mohammad, Mousavi, Sayed-Farhad, Karami, Hojat, Farzin, Saeed, Deo, Ravinesh, Othman, Faridah Binti, Chau, Kwok-Wing, Sarkamaryan, Saeed, Singh, Vijay P. and El-Shafie, Ahmed. 2018. "Bat algorithm for dam–reservoir operation." Environmental Earth Sciences. 77 (13), pp. 1-15. https://doi.org/10.1007/s12665-018-7662-5

Characteristics of ecosystem water use efficiency in a desert riparian forest

Ma, Xiaohong, Feng, Qi, Su, Yonghong, Yu, Tengfei and Deo, Ravinesh C.. 2018. "Characteristics of ecosystem water use efficiency in a desert riparian forest." Environmental Earth Sciences. 77 (358). https://doi.org/10.1007/s12665-018-7518-z

The influence of climatic inputs on stream-flow pattern forecasting: case study of Upper Senegal River

Diop, Lamine, Bodian, Ansoumana, Djaman, Koffi, Yaseen, Zaher Mundher, Deo, Ravinesh C., El-Shafie, Ahmed and Brown, Larry C.. 2018. "The influence of climatic inputs on stream-flow pattern forecasting: case study of Upper Senegal River." Environmental Earth Sciences. 77 (5). https://doi.org/10.1007/s1266

Uncertainty assessment of the multilayer perceptron (MLP) neural network model with implementation of the novel hybrid MLP-FFA method for prediction of biochemical oxygen demand and dissolved oxygen: a case study of Langat River

Raheli, Bahare, Aalami, Mohammad Taghi, El-Shafie, Ahmed, Ghorbani, Mohammad Ali and Deo, Ravinesh C.. 2017. "Uncertainty assessment of the multilayer perceptron (MLP) neural network model with implementation of the novel hybrid MLP-FFA method for prediction of biochemical oxygen demand and dissolved oxygen: a case study of Langat River." Environmental Earth Sciences. 76 (14). https://doi.org/10.1007/s12665-017-6842-z

Novel hybrid deep learning model for satellite based PM10 forecasting in the most polluted Australian hotspots

Sharma, Ekta, Deo, Ravinesh C., Soar, Jeffrey, Prasad, Ramendra, Parisi, Alfio V. and Raj, Nawin. 2022. "Novel hybrid deep learning model for satellite based PM10 forecasting in the most polluted Australian hotspots." Atmospheric Environment. 279, pp. 1-13. https://doi.org/10.1016/j.atmosenv.2022.119111

New double decomposition deep learning methods for river water level forecasting

Ahmed, A. A. Masrur, Deo, Ravinesh C., Ghahramani, Afshin, Feng, Qi, Raj, Nawin, Yin, Zhenliang and Yang, Linshan. 2022. "New double decomposition deep learning methods for river water level forecasting." Science of the Total Environment. 831, pp. 1-21. https://doi.org/10.1016/j.scitotenv.2022.154722

Development and evaluation of hybrid deep learning long short-term memory network model for pan evaporation estimation trained with satellite and ground-based data

Jayasinghe, W. J. M. Lakmini Prarthana, Deo, Ravinesh C., Ghahramani, Afshin, Ghimire, Sujan and Raj, Nawin. 2022. "Development and evaluation of hybrid deep learning long short-term memory network model for pan evaporation estimation trained with satellite and ground-based data." Journal of Hydrology. 607, pp. 1-19. https://doi.org/10.1016/j.jhydrol.2022.127534

Wind speed forecasting in Nepal using self-organizing map-based online sequential extreme learning machine

Sharma, Neelesh and Deo, Ravinesh. 2021. "Wind speed forecasting in Nepal using self-organizing map-based online sequential extreme learning machine." Deo, Ravinesh, Samui, Pijush and Roy, Sanjiban Sekhar (ed.) Predictive Modelling for Energy Management and Power Systems Engineering. Netherlands. Elsevier. pp. 437-484

Support vector machine model for multistep wind speed forecasting

Prasad, Shobna Mohini Mala, Nguyen-Huy, Thong and Deo, Ravinesh. 2021. "Support vector machine model for multistep wind speed forecasting." Deo, Ravinesh, Samui, Pijush and Roy, Sanjiban Sekhar (ed.) Predictive modelling for energy management and power systems engineering. Netherlands. Elsevier. pp. 335-389

Application of deep learning models for automated identification of Parkinson’s disease: a review (2011–2021)

Loh, Hui Wen, Hong, Wanrong, Ooi, Chui Ping, Chakraborty, Subrata, Barua, Prabal Datta, Deo, Ravinesh C., Soar, Jeffrey, Palmer, Elizabeth E. and Acharya, U. Rajendra. 2021. "Application of deep learning models for automated identification of Parkinson’s disease: a review (2011–2021)." Sensors. 21, pp. 1-27. https://doi.org/10.3390/s21217034

Artificial intelligence models for suspended river sediment prediction: state-of-the art, modeling framework appraisal, and proposed future research directions

Tao, Hai, Al-Khafaji, Zainab S., Qi, Chongchong, Zounemat-Kermani, Mohammad, Kisi, Ozgur, Tiyasha, Tiyasha, Chau, Kwok-Wing, Nourani, Vahid, Melesse, Assefa M., Elhakeem, Mohamed, Farooque, Aitazaz Ahsan, Nejadhashemi, A. Pouyan, Khedher, Khaled Mohamed, Alawi, Omer A., Deo, Ravinesh C., Shahid, Shamsuddin, Singh, Vijay P. and Yaseen, Zaher Mundher. 2021. "Artificial intelligence models for suspended river sediment prediction: state-of-the art, modeling framework appraisal, and proposed future research directions." Engineering Applications of Computational Fluid Mechanics. 15 (1), pp. 1585-1612. https://doi.org/10.1080/19942060.2021.1984992

Classification of catchments for nitrogen using Artificial Neural Network Pattern Recognition and spatial data

O'Sullivan, Cherie M., Ghahramani, Afshin, Deo, Ravinesh C., Pembleton, Keith, Khan, Urooj and Tuteja, Narendra. 2022. "Classification of catchments for nitrogen using Artificial Neural Network Pattern Recognition and spatial data." Science of the Total Environment. 809, pp. 1-15. https://doi.org/10.1016/j.scitotenv.2021.151139

Advanced extreme learning machines vs. deep learning models for peak wave energy period forecasting: A case study in Queensland, Australia

Ali, Mumtaz, Prasad, Ramendra, Xiang, Yong, Sankaran, Adarsh, Deo, Ravinesh C., Xiao, Fuyuan and Zhu, Shuyu. 2021. "Advanced extreme learning machines vs. deep learning models for peak wave energy period forecasting: A case study in Queensland, Australia." Renewable Energy. 177, pp. 1033-1044. https://doi.org/10.1016/j.renene.2021.06.052

Novel short-term solar radiation hybrid model: long short-term memory network integrated with robust local mean decomposition

Huynh, Anh Ngoc-Lan, Deo, Ravinesh C., Ali, Mumtaz, Abdulla, Shahab and Raj, Nawin. 2021. "Novel short-term solar radiation hybrid model: long short-term memory network integrated with robust local mean decomposition." Applied Energy. 298, pp. 1-19. https://doi.org/10.1016/j.apenergy.2021.117193

Evaluating management strategies for sustainable crop production under changing climate conditions: a system dynamics approach

Pham, Yen Hoang, Reardon-Smith, Kathryn and Deo, Ravinesh C.. 2021. "Evaluating management strategies for sustainable crop production under changing climate conditions: a system dynamics approach." Journal of Environmental Management. 292. https://doi.org/10.1016/j.jenvman.2021.112790

An interplay of soil salinization and groundwater degradation threatening coexistence of oasis-desert ecosystems

Yin, Xinwei, Feng, Qi, Li, Yan, Deo, Ravinesh C., Liu, Wei, Zhu, Meng, Zheng, Xinjun and Liu, Ran. 2022. "An interplay of soil salinization and groundwater degradation threatening coexistence of oasis-desert ecosystems." Science of the Total Environment. 806 (2), pp. 1-20. https://doi.org/10.1016/j.scitotenv.2021.150599

Hybrid deep learning method for a week-ahead evapotranspiration forecasting

Ahmed, A. A. Masrur, Deo, Ravinesh C., Feng, Qi, Ghahramani, Afshin, Raj, Nawin, Yin, Zhenliang and Yang, Linshan. 2022. "Hybrid deep learning method for a week-ahead evapotranspiration forecasting." Stochastic Environmental Research and Risk Assessment. 36 (3), pp. 831-849. https://doi.org/10.1007/s00477-021-02078-x

Streamflow prediction using an integrated methodology based on convolutional neural network and long short‑term memory networks

Ghimire, Sujan, Yaseen, Zaher Mundher, Farooque, Aitazaz A., Deo, Ravinesh C., Zhang, Ji and Tao, Xiaohui. 2021. "Streamflow prediction using an integrated methodology based on convolutional neural network and long short‑term memory networks." Scientific Reports. 11, pp. 1-26. https://doi.org/10.1038/s41598-021-96751-4

The role of internal transcribed spacer 2 secondary structures in classifying mycoparasitic Ampelomyces

Prahl, Rosa E., Khan, Shahjahan and Deo, Ravinesh C.. 2021. "The role of internal transcribed spacer 2 secondary structures in classifying mycoparasitic Ampelomyces." PLoS One. 16 (6), pp. 1-28. https://doi.org/10.1371/journal.pone.0253772

Deep Learning Forecasts of Soil Moisture: Convolutional Neural Network and Gated Recurrent Unit Models Coupled with Satellite-Derived MODIS, Observations and Synoptic-Scale Climate Index Data

Ahmed, A. A. Masrur, Deo, Ravinesh C., Raj, Nawin, Ghahramani, Afshin, Feng, Qi, Yin, Zhenliang and Yang, Linshan. 2021. "Deep Learning Forecasts of Soil Moisture: Convolutional Neural Network and Gated Recurrent Unit Models Coupled with Satellite-Derived MODIS, Observations and Synoptic-Scale Climate Index Data." Remote Sensing. 13 (4), pp. 1-30. https://doi.org/10.3390/rs13040554

LSTM integrated with Boruta-random forest optimiser for soil moisture estimation under RCP4.5 and RCP8.5 global warming scenarios

Ahmed, A. A. Masrur, Deo, Ravinesh C., Ghahramani, Afshin, Raj, Nawin, Feng, Qi, Yin, Zhenliang and Yang, Linshan. 2021. "LSTM integrated with Boruta-random forest optimiser for soil moisture estimation under RCP4.5 and RCP8.5 global warming scenarios." Stochastic Environmental Research and Risk Assessment. 35, pp. 1851-1881. https://doi.org/10.1007/s00477-021-01969-3

A new framework for classification of multi-category hand grasps using EMG signals

Miften, Firas Sabar, Diykh, Mohammed, Abdulla, Shahab, Siuly, Siuly, Green, Jonathan H. and Deo, Ravinesh C.. 2021. "A new framework for classification of multi-category hand grasps using EMG signals." Artificial Intelligence in Medicine. 112, pp. 1-14. https://doi.org/10.1016/j.artmed.2020.102005

Deep learning hybrid model with Boruta-Random forest optimiser algorithm for streamflow forecasting with climate mode indices, rainfall, and periodicity

Ahmed, A. A. Masrur, Deo, Ravinesh C., Feng, Qi, Ghahramani, Afshin, Raj, Nawin, Yin, Zhenliang and Yang, Linshan. 2021. "Deep learning hybrid model with Boruta-Random forest optimiser algorithm for streamflow forecasting with climate mode indices, rainfall, and periodicity." Journal of Hydrology. 599, pp. 1-23. https://doi.org/10.1016/j.jhydrol.2021.126350

Modeling soil temperature using air temperature features in diverse climatic conditions with complementary machine learning models

Bayatvarkeshi, Maryam, Bhagat, Suraj Kumar, Mohammadi, Kourosh, Kisi, Ozgur, Farahani, M., Hasani, A., Deo, Ravinesh and Yaseen, Zaher Mundher. 2021. "Modeling soil temperature using air temperature features in diverse climatic conditions with complementary machine learning models." Computers and Electronics in Agriculture. 185. https://doi.org/10.1016/j.compag.2021.106158

Mapping rice area and yield in northeastern asia by incorporating a crop model with dense vegetation index profiles from a geostationary satellite

Yeom, Jong-Min, Jeong, Seungtaek, Deo, Ravinesh C. and Ko, Jonghan. 2021. "Mapping rice area and yield in northeastern asia by incorporating a crop model with dense vegetation index profiles from a geostationary satellite." GIScience and Remote Sensing. https://doi.org/10.1080/15481603.2020.1853352

Deep Air Quality Forecasts: Suspended Particulate Matter Modeling With Convolutional Neural and Long Short-Term Memory Networks

Sharma, Ekta, Deo, Ravinesh C., Prasad, Ramendra, Parisi, Alfio and Raj, Nawin. 2020. "Deep Air Quality Forecasts: Suspended Particulate Matter Modeling With Convolutional Neural and Long Short-Term Memory Networks." IEEE Access. 8, pp. 209503-209516. https://doi.org/10.1109/ACCESS.2020.3039002

MARS model for prediction of short- and long-term global solar radiation

Balalla, Dilki T., Nguyen-Huy, Thong and Deo, Ravinesh. 2021. "MARS model for prediction of short- and long-term global solar radiation." Deo, Ravinesh, Roy, Sanjiban Sekhar and Samui, Pijush (ed.) Predictive Modelling for Energy Management and Power Systems Engineering. United Kingdom. Elsevier. pp. 391-436

Developing reservoir evaporation predictive model for successful dam management

Allawi, Mohammed Falah, Ahmed, Mohammed Lateef, Aidan, Ibraheem Abdallah, Deo, Ravinesh C. and El-Shafie, Ahmed. 2021. "Developing reservoir evaporation predictive model for successful dam management." Stochastic Environmental Research and Risk Assessment. 35 (2), pp. 499-514. https://doi.org/10.1007/s00477-020-01918-6

Application of effective drought index for quantification of meteorological drought events: a case study in Australia

Deo, Ravinesh C., Byun, Hi-Ryong, Adamowski, Jan F. and Begum, Khaleda. 2017. "Application of effective drought index for quantification of meteorological drought events: a case study in Australia." Theoretical and Applied Climatology. 128 (1-2), pp. 359-379. https://doi.org/10.1007/s00704-015-1706-5

Feedback modelling of the impacts of drought: A case study in coffee production systems in Viet Nam

Pham, Yen, Reardon-Smith, Kathryn, Mushtaq, Shahbaz and Deo, Ravinesh C.. 2020. "Feedback modelling of the impacts of drought: A case study in coffee production systems in Viet Nam." Climate Risk Management. 30, pp. 1-17. https://doi.org/10.1016/j.crm.2020.100255

Forecasting long-term precipitation for water resource management: a new multi-step data-intelligent modelling approach

Ali, Mumtaz, Deo, Ravinesh C., Xiang, Yong, Li, Ya and Yaseen, Zaher Mundher. 2020. "Forecasting long-term precipitation for water resource management: a new multi-step data-intelligent modelling approach." Hydrological Sciences Journal. 65 (16), pp. 2693-2708. https://doi.org/10.1080/02626667.2020.1808219

Development of Flood Monitoring Index for daily flood risk evaluation: case studies in Fiji

Moishin, Mohammed, Deo, Ravinesh C., Prasad, Ramendra, Raj, Nawin and Abdulla, Shahab. 2021. "Development of Flood Monitoring Index for daily flood risk evaluation: case studies in Fiji." Stochastic Environmental Research and Risk Assessment. 35 (7), pp. 1387-1402. https://doi.org/10.1007/s00477-020-01899-6

The modeling of human facial pain intensity based on Temporal Convolutional Networks trained with video frames in HSV color space

Bargshady, Ghazal, Zhou, Xujuan, Deo, Ravinesh C., Soar, Jeffrey, Whittaker, Frank and Wang, Hua. 2020. "The modeling of human facial pain intensity based on Temporal Convolutional Networks trained with video frames in HSV color space." Applied Soft Computing. 97 (Part A), pp. 1-14. https://doi.org/10.1016/j.asoc.2020.106805

Modeling wheat yield with data-intelligent algorithms: artificial neural network versus genetic programming and minimax probability machine regression

Ali, Mumtaz and Deo, Ravinesh C.. 2020. "Modeling wheat yield with data-intelligent algorithms: artificial neural network versus genetic programming and minimax probability machine regression." Samui, Pijush, Bui, Dieu Tien, Chakraborty, Subrata and Deo, Ravinesh C. (ed.) Handbook of probabilistic models. Oxford, United Kingdom. Elsevier. pp. 37-87

MARS model for prediction of short- and long-term global solar radiation

Balalla, Dilki T., Nguyen-Huy, Thong and Deo, Ravinesh. 2021. "MARS model for prediction of short- and long-term global solar radiation." Deo, Ravinesh, Samui, Pijush and Roy, Sanjiban Sekhar (ed.) Predictive modelling for energy management and power systems engineering. Amsterdam, Netherlands. Elsevier. pp. 391-436

Short-term electrical energy demand prediction under heat island effects using emotional neural network integrated with genetic algorithm

Karalasingham, Sagthitharan, Deo, Ravinesh and Prasad, Ramendra. 2021. "Short-term electrical energy demand prediction under heat island effects using emotional neural network integrated with genetic algorithm." Deo, Ravinesh, Samui, Pijush and Roy, Sanjiban Sekhar (ed.) Predictive modelling for energy management and power systems engineering. Amsterdam, Netherlands. Elsevier. pp. 271-298

Hybrid multilayer perceptron-firefly optimizer algorithm for modelling photosynthetic active solar radiation for biofuel energy exploration

Goundar, Harshna, Yaseen, Zaher Mundher and Deo, Ravinesh. 2021. "Hybrid multilayer perceptron-firefly optimizer algorithm for modelling photosynthetic active solar radiation for biofuel energy exploration." Deo, Ravinesh, Samui, Pijush and Roy, Sanjiban Sekhar (ed.) Predictive modelling for energy management and power systems engineering. Amsterdam, Netherlands. Elsevier. pp. 191-232

Development of data-driven models for wind speed forecasting in Australia

Neupane, Ananta, Raj, Nawin, Deo, Ravinesh and Ali, Mumtaz. 2021. "Development of data-driven models for wind speed forecasting in Australia." Deo, R., Samui, Pijush and Roy, Sanjiban Sekhar (ed.) Predictive modelling for energy management and power systems engineering. Netherlands. Elsevier. pp. 143-190

Design and performance of two decomposition paradigms in forecasting daily solar radiation with evolutionary polynomial regression: wavelet transform versus ensemble empirical mode decomposition

Rezaie-Balf, Mohammad, Kim, Sungwon, Ghaemi, Alireza and Deo, Ravinesh. 2021. "Design and performance of two decomposition paradigms in forecasting daily solar radiation with evolutionary polynomial regression: wavelet transform versus ensemble empirical mode decomposition." Deo, Ravinesh, Samui, Pijush and Roy, Sanjiban Sekhar (ed.) Predictive modelling for energy management and power systems engineering. Amsterdam, Netherlands. Elsevier. pp. 115-142

Experimental Study on the Rainfall-Runoff Responses of Typical Urban Surfaces and Two Green Infrastructures Using Scale-Based Models

Liu, Wen, Feng, Qi, Deo, Ravinesh C., Yao, Lei and Wei, Wei. 2020. "Experimental Study on the Rainfall-Runoff Responses of Typical Urban Surfaces and Two Green Infrastructures Using Scale-Based Models ." Environmental Management (New York): an international journal for decision-makers, scientists and environmental auditors. 66 (4), pp. 683-693. https://doi.org/10.1007/s00267-020-01339-9

Ensemble neural network approach detecting pain intensity from facial expressions

Bargshady, Ghazal, Zhou, Xujuan, Deo, Ravinesh C., Soar, Jeffrey, Whittaker, Frank and Wang, Hua. 2020. "Ensemble neural network approach detecting pain intensity from facial expressions." Artificial Intelligence in Medicine. 109, pp. 1-12. https://doi.org/10.1016/j.artmed.2020.101954

Daily flood forecasts with intelligent data analytic models: multivariate empirical mode decomposition-based modeling methods

Prasad, Ramendra, Charan, Dhrishna, Joseph, Lionel, Nguyen-Huy, Thong, Deo, Ravinesh C. and Singh, Sanjay. 2021. "Daily flood forecasts with intelligent data analytic models: multivariate empirical mode decomposition-based modeling methods." Deo, Ravinesh C., Samui, Pijush, Kisi, Ozgur and Yaseen, Zaher Mundher (ed.) Intelligent data analytics for decision-support systems in hazard mitigation: theory and practice of hazard mitigation. Singapore. Springer. pp. 359-381

Artificial neural networks for prediction of Steadman Heat Index

Chand, Bhuwan, Nguyen-Huy, Thong and Deo, Ravinesh C.. 2021. "Artificial neural networks for prediction of Steadman Heat Index." Deo, Ravinesh C., Samui, Pijush, Kisi, Ozgur and Yaseen, Zaher Mundher (ed.) Intelligent data analytics for decision-support systems in hazard mitigation: theory and practice of hazard mitigation. Singapore. Springer. pp. 293-357

Spatial prediction of landslide susceptibility using random forest algorithm

Rahmati, Omid, Kornejady, Aiding and Deo, Ravinesh C.. 2021. "Spatial prediction of landslide susceptibility using random forest algorithm." Deo, Ravinesh C., Samui, Pijush, Kisi, Ozgur and Yaseen, Zaher Mundher (ed.) Intelligent data analytics for decision-support systems in hazard mitigation: theory and practice of hazard mitigation. Singapore. Springer. pp. 281-292

Intelligent data analytics for time series, trend analysis and drought indices comparison

Dayal, Kavina S., Deo, Ravinesh C. and Apan, Armando A.. 2021. "Intelligent data analytics for time series, trend analysis and drought indices comparison." Deo, Ravinesh C., Samui, Pijush, Kisi, Ozgur and Yaseen, Zaher Mundher (ed.) Intelligent data analytics for decision-support systems in hazard mitigation: theory and practice of hazard mitigation. Singapore. Springer. pp. 151-169

Modulation of tropical cyclone genesis by Madden–Julian Oscillation in the Southern Hemisphere

Dayal, Kavina S., Wang, Bin and Deo, Ravinesh C.. 2021. "Modulation of tropical cyclone genesis by Madden–Julian Oscillation in the Southern Hemisphere." Deo, Ravinesh C., Samui, Pijush, Kisi, Ozgur and Yaseen, Zaher Mundher (ed.) Intelligent data analytics for decision-support systems in hazard mitigation: theory and practice of hazard mitigation. Singapore. Springer. pp. 127-150

Bayesian Markov Chain Monte Carlo-based copulas: factoring the role of large-scale climate indices in monthly flood prediction

Nguyen-Huy, Thong, Deo, Ravinesh C., Yaseen, Zaher Mundher, Mushtaq, Shahbaz and Prasad, Ramendra. 2021. "Bayesian Markov Chain Monte Carlo-based copulas: factoring the role of large-scale climate indices in monthly flood prediction." Deo, Ravinesh C., Samui, Pijush, Kisi, Ozgur and Yaseen, Zaher Mundher (ed.) Intelligent data analytics for decision-support systems in hazard mitigation: theory and practice of hazard mitigation. Singapore. Springer. pp. 29-47

Intelligent data analytics for decision-support systems in hazard mitigation: theory and practice of hazard mitigation

Deo, Ravinesh C., Samui, Pijush, Kisi, Ozgur and Yaseen, Zaher Mundher. 2021. Intelligent data analytics for decision-support systems in hazard mitigation: theory and practice of hazard mitigation. Singapore. Springer.

Near real-time significant wave height forecasting with hybridized multiple linear regression algorithms

Ali, Mumtaz, Prasad, Ramendra, Xiang, Yong and Deo, Ravinesh C.. 2020. "Near real-time significant wave height forecasting with hybridized multiple linear regression algorithms." Renewable and Sustainable Energy Reviews. 132. https://doi.org/10.1016/j.rser.2020.110003

Electrical Energy Demand Forecasting Model Development and Evaluation with Maximum Overlap Discrete Wavelet Transform-Online Sequential Extreme Learning Machines Algorithms

Al-Musaylh, Mohanad S., Deo, Ravinesh C. and Li, Yan. 2020. "Electrical Energy Demand Forecasting Model Development and Evaluation with Maximum Overlap Discrete Wavelet Transform-Online Sequential Extreme Learning Machines Algorithms." Energies. 13 (9). https://doi.org/10.3390/en13092307

Near real-time global solar radiation forecasting at multiple time-step horizons using the long short-term memory network

Huynh, Anh Ngoc‐Lan, Deo, Ravinesh C., An-Vo, Duc-Anh, Ali, Mumtaz, Raj, Nawin and Abdulla, Shahab. 2020. "Near real-time global solar radiation forecasting at multiple time-step horizons using the long short-term memory network." Energies. 13 (14). https://doi.org/10.3390/en13143517

Adaptive boost LS-SVM classification approach for time-series signal classification in epileptic seizure diagnosis applications

Al-Hadeethi, Hanan, Abdulla, Shahab, Diykh, Mohammed, Deo, Ravinesh C. and Green, Jonathan H.. 2020. "Adaptive boost LS-SVM classification approach for time-series signal classification in epileptic seizure diagnosis applications." Expert Systems with Applications. 161. https://doi.org/10.1016/j.eswa.2020.113676

Random forest predictive model development with uncertainty analysis capability for the estimation of evapotranspiration in an arid oasis region

Wu, Min, Feng, Qi, Wen, Xiaohu, Deo, Ravinesh C., Yin, Zhenliang, Yang, Linshan and Sheng, Danrui. 2020. "Random forest predictive model development with uncertainty analysis capability for the estimation of evapotranspiration in an arid oasis region." Hydrology Research: an international journal. 51 (4), pp. 648-665. https://doi.org/10.2166/nh.2020.012

An ensemble tree-based machine learning model for predicting the uniaxial compressive strength of travertine rocks

Barzegar, Rahim, Sattarpour, Masoud, Deo, Ravinesh, Fijani, Elham and Adamowski, Jan. 2020. "An ensemble tree-based machine learning model for predicting the uniaxial compressive strength of travertine rocks." Neural Computing and Applications. 32 (13), pp. 9065-9080. https://doi.org/10.1007/s00521-019-04418-z

Stormwater runoff and pollution retention performances of permeable pavements and the effects of structural factors

Liu, Wen, Feng, Qi, Chen, Weiping and Deo, Ravinesh C.. 2020. "Stormwater runoff and pollution retention performances of permeable pavements and the effects of structural factors." Environmental Science and Pollution Research. 27 (24), pp. 30831-30843. https://doi.org/10.1007/s11356-020-09220-2

Spatial mapping of short-term solar radiation prediction incorporating geostationary satellite images coupled with deep convolutional LSTM networks for South Korea

Yeom, Jong-Min, Deo, Ravinesh C., Adamowski, Jan F., Park, Seonyoung and Lee, Chang-Suk. 2020. "Spatial mapping of short-term solar radiation prediction incorporating geostationary satellite images coupled with deep convolutional LSTM networks for South Korea." Environmental Research Letters. 15 (9), pp. 1-10. https://doi.org/10.1088/1748-9326/ab9467

Integrative stochastic model standardization with genetic algorithm for rainfall pattern forecasting in tropical and semi-arid environments

Salih, Sinan Q., Sharafati, Ahmad, Ebtehaj, Isa, Sanikhani, Hadi, Siddique, Ridwan, Deo, Ravinesh C., Bonakdari, Hossein, Shahid, Shamsuddin and Yaseen, Zaher Mundher. 2020. "Integrative stochastic model standardization with genetic algorithm for rainfall pattern forecasting in tropical and semi-arid environments." Hydrological Sciences Journal. 65 (7), pp. 1145-1157. https://doi.org/10.1080/02626667.2020.1734813

Hybridized neural fuzzy ensembles for dust source modeling and prediction

Rahmati, Omid, Panahi, Mahdi, Ghiasi, Seid Saeid, Deo, Ravinesh C., Tiefenbacher, John P., Pradhan, Biswajeet, Jahani, Ali, Goshtasb, Hamid, Kornejady, Aiding, Shahabi, Himan, Shirzadi, Ataollah, Khosravi, Hassan, Moghaddam, Davoud Davoudi, Mohtashamian, Maryamsadat and Bui, Dieu Tien. 2020. "Hybridized neural fuzzy ensembles for dust source modeling and prediction." Atmospheric Environment. 224, pp. 1-11. https://doi.org/10.1016/j.atmosenv.2020.117320

Global solar radiation estimation and climatic variability analysis using extreme learning machine based predictive model

Tao, Hai, Sharafati, Ahmad, Mohammed, Achite, Salih, Sinan Q., Deo, Ravinesh C., Al-Ansari, Nadhir and Yaseen, Zaher Mundher. 2020. "Global solar radiation estimation and climatic variability analysis using extreme learning machine based predictive model." IEEE Access. 8, pp. 12026-12042. https://doi.org/10.1109/ACCESS.2020.2965303

Development and evaluation of the cascade correlation neural network and the random forest models for river stage and river flow prediction in Australia

Ghorbani, Mohammad Ali, Deo, Ravinesh C., Kim, Sungwon, Kashani, Mahasa Hasanpour, Karimi, Vahid and Izadkhah, Maryam. 2020. "Development and evaluation of the cascade correlation neural network and the random forest models for river stage and river flow prediction in Australia." Soft Computing. 24, pp. 12079-12090. https://doi.org/10.1007/s00500-019-04648-2

Causality of climate, food production and conflict over the last two millennia in the Hexi Corridor, China

Yang, Linshan, Feng, Qi, Adamowski, Jan F., Deo, Ravinesh C., Yin, Zhenlaing, Wen, Xiaohu, Tang, Xia and Wu, Min. 2020. "Causality of climate, food production and conflict over the last two millennia in the Hexi Corridor, China." Science of the Total Environment. 713, pp. 1-11. https://doi.org/10.1016/j.scitotenv.2020.136587

Mixing characteristics of a film-exciting flapping jet

Wu, M., Xu, M., Mi, J. and Deo, R. C.. 2020. "Mixing characteristics of a film-exciting flapping jet." International Journal of Heat and Fluid Flow. 82, pp. 1-9. https://doi.org/10.1016/j.ijheatfluidflow.2019.108532

Enhanced deep learning algorithm development to detect pain intensity from facial expression images

Bargshady, Ghazal, Zhou, Xujuan, Deo, Ravinesh C., Soar, Jeffery, Whittaker, Frank and Wang, Hua. 2020. "Enhanced deep learning algorithm development to detect pain intensity from facial expression images." Expert Systems with Applications. 149, pp. 1-10. https://doi.org/10.1016/j.eswa.2020.113305

A general extensible learning approach for multi-disease recommendations in a telehealth environment

Lafta, Raid, Zhang, Ji, Tao, Xiaohui, Zhu, Xiaodong, Li, Hongzhou, Chang, Liang and Deo, Ravinesh. 2020. "A general extensible learning approach for multi-disease recommendations in a telehealth environment ." Pattern Recognition Letters. 132, pp. 106-114. https://doi.org/10.1016/j.patrec.2018.11.006

A hybrid air quality early-warning framework: an hourly forecasting model with online sequential extreme learning machines and empirical mode decomposition algorithms

Sharma, Ekta, Deo, Ravinesh C., Prasad, Ramendra and Parisi, Alfio V.. 2020. "A hybrid air quality early-warning framework: an hourly forecasting model with online sequential extreme learning machines and empirical mode decomposition algorithms." Science of the Total Environment. 709, pp. 1-23. https://doi.org/10.1016/j.scitotenv.2019.135934

Machine learning approaches for spatial modeling of agricultural droughts in the south-east region of Queensland Australia

Rahmati, Omid, Falah, Fatemeh, Dayal, Kavina Shaanu, Deo, Ravinesh C., Mohammadi, Farnoush, Biggs, Trent, Moghaddam, Davoud Davoudi, Naghibi, Seyed Amir and Bui, Dieu Tien. 2020. "Machine learning approaches for spatial modeling of agricultural droughts in the south-east region of Queensland Australia." Science of the Total Environment. 699 (134230). https://doi.org/10.1016/j.scitotenv.2019.134230

Projected spatial patterns in precipitation and air temperature for China's northwest region derived from high‐resolution regional climate models

Yin, Zhenliang, Feng, Qi, Yang, Linshan, Deo, Ravinesh C., Adamowski, Jan F., Wen, Xiaohu, Jia, Bing and Si, Jianhua. 2020. "Projected spatial patterns in precipitation and air temperature for China's northwest region derived from high‐resolution regional climate models." International Journal of Climatology. 40 (8), pp. 3922-3941. https://doi.org/10.1002/joc.6435

Exploring solar and wind energy resources in North Korea with COMS MI geostationary satellite data coupled with numerical weather prediction reanalysis variables

Yeom, Jong-Min, Deo, Ravinesh, Adamowski, Jan F., Chae, Taebyeong, Kim, Dong-Su, Han, Kyung-Soo and Kim, Do-Yong. 2020. "Exploring solar and wind energy resources in North Korea with COMS MI geostationary satellite data coupled with numerical weather prediction reanalysis variables." Renewable and Sustainable Energy Reviews. 119, pp. 1-14. https://doi.org/10.1016/j.rser.2019.109570

Capability and robustness of novel hybridized models used for drought hazard modeling in southeast Queensland, Australia

Rahmati, Omid, Panahi, Mahdi, Kalantari, Zahra, Soltani, Elinaz, Falah, Fatemeh, Dayal, Kavina S., Mohammadi, Farnoush, Deo, Ravinesh C., Tiefenbacher, John and Bui, Dieu Tien. 2020. "Capability and robustness of novel hybridized models used for drought hazard modeling in southeast Queensland, Australia." Science of the Total Environment. 718, pp. 1-17. https://doi.org/10.1016/j.scitotenv.2019.134656

Regional hydrology heterogeneity and the response to climate and land surface changes in arid alpine basin, northwest China

Yang, Linshan, Feng, Qi, Yin, Zhenliang, Deo, Ravinesh C., Wen, Xiaohu, Si, Jianhua and Liu, Wen. 2020. "Regional hydrology heterogeneity and the response to climate and land surface changes in arid alpine basin, northwest China." Catena. 187. https://doi.org/10.1016/j.catena.2019.104345

Modern artificial intelligence model development for undergraduate student performance prediction: an investigation on engineering mathematics courses

Deo, Ravinesh C., Yaseen, Zaher Mundher, Al-Ansari, Nadhir, Nguyen-Huy, Thong, Langlands, Trevor and Galligan, Linda. 2020. "Modern artificial intelligence model development for undergraduate student performance prediction: an investigation on engineering mathematics courses." IEEE Access. 8, pp. 136697-136724. https://doi.org/10.1109/ACCESS.2020.3010938

Correcting satellite precipitation data and assimilating satellite-derived soil moisture data to generate ensemble hydrological forecasts within the HBV rainfall-runoff model

Ciupak, Maurycy, Ozga-Zielinski, Bogdan, Adamowski, Jan, Deo, Ravinesh C and Kochanek, Krzysztof. 2019. "Correcting satellite precipitation data and assimilating satellite-derived soil moisture data to generate ensemble hydrological forecasts within the HBV rainfall-runoff model." Water: an open access journal. 11 (10), pp. 1-31. https://doi.org/10.3390/w11102138

Partitioning groundwater recharge sources in multiple aquifers system within a desert oasis environment: Implications for water resources management in endorheic basins

Guo, Xiaoyan, Feng, Qi, Si, Jianhua, Xi, Haiyang, Zhao, Yan and Deo, Ravinesh C.. 2019. "Partitioning groundwater recharge sources in multiple aquifers system within a desert oasis environment: Implications for water resources management in endorheic basins." Journal of Hydrology. 579, pp. 1-11. https://doi.org/10.1016/j.jhydrol.2019.124212

Handbook of probabilistic models

Deo, Ravinesh C.. Samui, Pijush, Bui, Dieu Tien, Chakraborty, Subrata and Deo, Ravinesh C. (ed.) 2020. Handbook of probabilistic models. Oxford, United Kingdom. Elsevier.

Probabilistic seasonal rainfall forecasts using semiparametric d-vine copula-based quantile regression

Nguyen-Huy, Thong, Deo, Ravinesh C., Mushtaq, Shahbaz and Khan, Shahjahan. 2020. "Probabilistic seasonal rainfall forecasts using semiparametric d-vine copula-based quantile regression." Samui, Pijush, Bui, Dieu Tien, Chakraborty, Subrata and Deo, Ravinesh C. (ed.) Handbook of probabilistic models. Oxford, United Kingdom. Elsevier. pp. 203-227

Monthly rainfall forecasting with Markov Chain Monte Carlo simulations integrated with statistical bivariate copulas

Ali, Mumtaz, Deo, Ravinesh C., Downs, Nathan J. and Maraseni, Tek. 2020. "Monthly rainfall forecasting with Markov Chain Monte Carlo simulations integrated with statistical bivariate copulas." Samui, Pijush, Bui, Dieu Tien, Chakraborty, Subrata and Deo, Ravinesh C. (ed.) Handbook of probabilistic models. Oxford, United Kingdom. Elsevier. pp. 89-105

Development of copula statistical drought prediction model using the Standardized Precipitation-Evapotranspiration Index

Dayal, Kavina S., Deo, Ravinesh C. and Apan, Armando A.. 2020. "Development of copula statistical drought prediction model using the Standardized Precipitation-Evapotranspiration Index." Samui, Pijush, Bui, Dieu Tien, Chakraborty, Subrata and Deo, Ravinesh C. (ed.) Handbook of probabilistic models. Oxford, United Kingdom. Elsevier. pp. 141-178

Soil organic carbon in semiarid alpine regions: the spatial distribution, stock estimation, and environmental controls

Zhu, Meng, Feng, Qi, Zhang, Mengxu, Liu, Wei, Deo, Ravinesh C., Zhang, Chengqi and Yang, Linshan. 2019. "Soil organic carbon in semiarid alpine regions: the spatial distribution, stock estimation, and environmental controls." Journal of Soils and Sediments: protection, risk assessment and remediation. 19 (10), pp. 3427-3441. https://doi.org/10.1007/s11368-019-02295-6

Controlling factors of plant community composition with respect to the slope aspect gradient in the Qilian Mountains

Qin, Yanyan, Adamowski, Jan F., Deo, Ravinesh C., Hu, Zeyong, Cao, Jianjun, Zhu, Meng and Feng, Qi. 2019. "Controlling factors of plant community composition with respect to the slope aspect gradient in the Qilian Mountains." Ecosphere. 10 (9), pp. 1-13. https://doi.org/10.1002/ecs2.2851

Grassland degradation on the Qinghai-Tibetan Plateau: reevaluation of causative factors

Cao, Jianjun, Adamowski, Jan F., Deo, Ravinesh C., Xu, Xueyun, Gong, Yifan and Feng, Qi. 2019. "Grassland degradation on the Qinghai-Tibetan Plateau: reevaluation of causative factors." Rangeland Ecology and Management. 72 (6), pp. 988-995. https://doi.org/10.1016/j.rama.2019.06.001

Fractal dimension undirected correlation graph-based support vector machine model for identification of focal and non-focal electroencephalography signals

Diykh, Mohammed, Abdulla, Shahab, Saleh, Khalid and Deo, Ravinesh C.. 2019. "Fractal dimension undirected correlation graph-based support vector machine model for identification of focal and non-focal electroencephalography signals." Biomedical Signal Processing and Control. 54, pp. 1-10. https://doi.org/10.1016/j.bspc.2019.101611

The impacts of substrate and vegetation on stormwater runoff quality from extensive green roofs

Liu, Wen, Wei, Wei, Chen, Weiping, Deo, Ravinesh C., Si, Jianhua, Xi, Haiyang, Li, Baofeng and Feng, Qi. 2019. "The impacts of substrate and vegetation on stormwater runoff quality from extensive green roofs." Journal of Hydrology. 576, pp. 575-582. https://doi.org/10.1016/j.jhydrol.2019.06.061

Application of multivariate recursive nesting bias correction, multiscale wavelet entropy and AI-based models to improve future precipitation projection in upstream of the Heihe River, Northwest China

Yang, Linshan, Feng, Qi, Yin, Zhenliang, Wen, Xiaohu, Deo, Ravinesh C., Si, Jianhua and Li, Changbin. 2019. "Application of multivariate recursive nesting bias correction, multiscale wavelet entropy and AI-based models to improve future precipitation projection in upstream of the Heihe River, Northwest China." Theoretical and Applied Climatology. 137 (1-2), pp. 323-339. https://doi.org/10.1007/s00704-018-2598-y

Wavelet-based 3-phase hybrid SVR model trained with satellite-derived predictors, particle swarm optimization and maximum overlap discrete wavelet transform for solar radiation prediction

Ghimire, Sujan, Deo, Ravinesh C., Raj, Nawin and Mi, Jianchun. 2019. "Wavelet-based 3-phase hybrid SVR model trained with satellite-derived predictors, particle swarm optimization and maximum overlap discrete wavelet transform for solar radiation prediction." Renewable and Sustainable Energy Reviews. 113, pp. 1-19. https://doi.org/10.1016/j.rser.2019.109247

Deep solar radiation forecasting with convolutional neural network and long short-term memory network algorithms

Ghimire, Sujan, Deo, Ravinesh C., Raj, Nawin and Mi, Jianchun. 2019. "Deep solar radiation forecasting with convolutional neural network and long short-term memory network algorithms." Applied Energy. 253, pp. 1-20. https://doi.org/10.1016/j.apenergy.2019.113541

Sleep EEG signal analysis based on correlation graph similarity coupled with an ensemble extreme machine learning algorithm

Abdulla, Shahab, Diykh, Mohammed, Lafta, Raid Luaibi, Saleh, Khalid and Deo, Ravinesh C.. 2019. "Sleep EEG signal analysis based on correlation graph similarity coupled with an ensemble extreme machine learning algorithm." Expert Systems with Applications. 138, pp. 1-15. https://doi.org/10.1016/j.eswa.2019.07.007

Short-term electricity demand forecasting using machine learning methods enriched with ground-based climate and ECMWF Reanalysis atmospheric predictors in southeast Queensland, Australia

Al-Musaylh, Mohanad S., Deo, Ravinesh C., Adamowski, Jan F. and Li, Yan. 2019. "Short-term electricity demand forecasting using machine learning methods enriched with ground-based climate and ECMWF Reanalysis atmospheric predictors in southeast Queensland, Australia." Renewable and Sustainable Energy Reviews. 113. https://doi.org/10.1016/j.rser.2019.109293

Designing a new data intelligence model for global solar radiation prediction: application of multivariate modeling scheme

Tao, Hai, Ebtehaj, Isa, Bonakdari, Hossein, Heddam, Salim, Voyant, Cyril, Al-Ansari, Nadhir, Deo, Ravinesh and Yaseen, Zaheer Mundher. 2019. "Designing a new data intelligence model for global solar radiation prediction: application of multivariate modeling scheme." Energies. 12 (7), pp. 1-24. https://doi.org/10.3390/en12071365

Incorporating synoptic-scale climate signals for streamflow modelling over the Mediterranean region using machine learning models

Kisi, Ozgur, Choubin, Bahram, Deo, Ravinesh C. and Yaseen, Zaheer Mundher. 2019. "Incorporating synoptic-scale climate signals for streamflow modelling over the Mediterranean region using machine learning models." Hydrological Sciences Journal. 64 (10), pp. 1240-1252. https://doi.org/10.1080/02626667.2019.1632460

Improving SPI-derived drought forecasts incorporating synoptic-scale climate indices in multi-phase multivariate empirical mode decomposition model hybridized with simulated annealing and kernel ridge regression algorithms

Ali, Mumtaz, Deo, Ravinesh C., Maraseni, Tek and Downs, Nathan J.. 2019. "Improving SPI-derived drought forecasts incorporating synoptic-scale climate indices in multi-phase multivariate empirical mode decomposition model hybridized with simulated annealing and kernel ridge regression algorithms." Journal of Hydrology. 576, pp. 164-184. https://doi.org/10.1016/j.jhydrol.2019.06.032

Deep Learning Neural Networks Trained with MODIS Satellite-Derived Predictors for Long-Term Global Solar Radiation Prediction

Ghimire, Sujan, Deo, Ravinesh C., Raj, Nawin and Mi, Jianchun. 2019. "Deep Learning Neural Networks Trained with MODIS Satellite-Derived Predictors for Long-Term Global Solar Radiation Prediction." Energies. 12 (12), pp. 1-42. https://doi.org/10.3390/en12122407

Situations, challenges and strategies of urban water management in Beijing under rapid urbanization effect

Liu, Wen, Chen, Weiping, Feng, Qi and Deo, Ravinesh C.. 2019. "Situations, challenges and strategies of urban water management in Beijing under rapid urbanization effect." Water Science and Technology: Water Supply. 19 (1), pp. 115-127. https://doi.org/10.2166/ws.2018.057

Suitable exclosure duration for the restoration of degraded alpine grasslands on the Qinghai-Tibetan Plateau

Cao, Jianjun, Li, Guangdong, Adamowski, Jan F., Holden, Nicolas M., Deo, Ravinesh C., Hu, Zeyong, Zhu, Guofeng, Xu, Xueyun and Feng, Qi. 2019. "Suitable exclosure duration for the restoration of degraded alpine grasslands on the Qinghai-Tibetan Plateau." Land Use Policy: the international journal covering all aspects of land use. 86, pp. 261-267. https://doi.org/10.1016/j.landusepol.2019.05.008

Environmental and economic impacts and trade-offs from simultaneous management of soil constraints, nitrogen and water

Kodur, Shreevatsa, Shrestha, Uttam Babu, Maraseni, Tek Narayan and Deo, Ravinesh C.. 2019. "Environmental and economic impacts and trade-offs from simultaneous management of soil constraints, nitrogen and water." Journal of Cleaner Production. 222, pp. 960-970. https://doi.org/10.1016/j.jclepro.2019.03.079

Land subsidence modelling using tree-based machine learning algorithms

Rahmati, Omid, Falah, Fatemeh, Naghibi, Seyed Amir, Biggs, Trent, Soltani, Milad, Deo, Ravinesh C., Cerda, Artemi, Mohammadi, Farnoush and Bui, Dieu Tien. 2019. "Land subsidence modelling using tree-based machine learning algorithms." Science of the Total Environment. 672, pp. 239-252. https://doi.org/10.1016/j.scitotenv.2019.03.496

Weekly soil moisture forecasting with multivariate sequential, ensemble empirical mode decomposition and Boruta-random forest hybridizer algorithm approach

Prasad, Ramendra, Deo, Ravinesh C., Li, Yan and Maraseni, Tek. 2019. "Weekly soil moisture forecasting with multivariate sequential, ensemble empirical mode decomposition and Boruta-random forest hybridizer algorithm approach." Catena. 177, pp. 149-166. https://doi.org/10.1016/j.catena.2019.02.012

Copula statistical models for analyzing stochastic dependencies of systemic drought risk and potential adaptation strategies

Nguyen-Huy, Thong, Deo, Ravinesh C., Mushtaq, Shahbaz, Kath, Jarrod and Khan, Shahjahan. 2019. "Copula statistical models for analyzing stochastic dependencies of systemic drought risk and potential adaptation strategies." Stochastic Environmental Research and Risk Assessment. 33 (3), pp. 779-799. https://doi.org/10.1007/s00477-019-01662-6

Effects of stand age on carbon storage in dragon spruce forest ecosystems in the upper reaches of the Bailongjiang River basin, China

Cao, Jianjun, Gong, Yifan, Adamowski, Jan F., Deo, Ravinesh C., Zhu, Guofeng, Dong, Xiaogang, Zhang, Xiaofang, Liu, Haibo and Xin, Cunlin. 2019. "Effects of stand age on carbon storage in dragon spruce forest ecosystems in the upper reaches of the Bailongjiang River basin, China." Scientific Reports. 9 (1), pp. 1-11. https://doi.org/10.1038/s41598-019-39626-z

The role of topography in shaping the spatial patterns of soil organic carbon

Zhu, Meng, Feng, Qi, Qin, Yanyan, Cao, Jiajun, Zhang, Mengxu, Liu, Wei, Deo, Ravinesh C., Zhang, Chengqi, Li, Ruolin and Li, Baofeng. 2019. "The role of topography in shaping the spatial patterns of soil organic carbon." Catena. 176, pp. 296-305. https://doi.org/10.1016/j.catena.2019.01.029

PMT: new analytical framework for automated evaluation of geo-environmental modelling approaches

Rahmati, Omid, Kornejady, Aiding, Samadi, Mahmood, Deo, Ravinesh C., Conoscenti, Christian, Lombardo, Luigi, Dayal, Kavina, Taghizadeh-Mehrjardi, Ruhollah, Pourghasemi, Hamid Reza, Kumar, Sandeep and Bui, Dieu Tien. 2019. "PMT: new analytical framework for automated evaluation of geo-environmental modelling approaches." Science of the Total Environment. 664, pp. 296-311. https://doi.org/10.1016/j.scitotenv.2019.02.017

Universally deployable extreme learning machines integrated with remotely sensed MODIS satellite predictors over Australia to forecast global solar radiation: a new approach

Deo, Ravinesh C., Sahin, Mehmet, Adamowski, Jan F. and Mi, Jianchun. 2019. "Universally deployable extreme learning machines integrated with remotely sensed MODIS satellite predictors over Australia to forecast global solar radiation: a new approach." Renewable and Sustainable Energy Reviews. 104, pp. 235-261. https://doi.org/10.1016/j.rser.2019.01.009

Two-phase extreme learning machines integrated with the complete ensemble empirical mode decomposition with adaptive noise algorithm for multi-scale runoff prediction problems

Wen, Xiaohu, Feng, Qi, Deo, Ravinesh C., Wu, Min, Yin, Zhenliang, Yang, Linshan and Singh, Vijay P.. 2019. "Two-phase extreme learning machines integrated with the complete ensemble empirical mode decomposition with adaptive noise algorithm for multi-scale runoff prediction problems." Journal of Hydrology. 570, pp. 167-184. https://doi.org/10.1016/j.jhydrol.2018.12.060

New approach for sediment yield forecasting with a two-phase feed forward neuron network-particle swarm optimization model integrated with the gravitational search algorithm

Meshram, Sarita Gajbhiye, Ghorbani, M. A., Deo, Ravinesh C., Kashani, Mahsa Hasanpour, Meshram, Chandrashekhar and Karimi, Vahid. 2019. "New approach for sediment yield forecasting with a two-phase feed forward neuron network-particle swarm optimization model integrated with the gravitational search algorithm." Water Resources Management. 33 (7), pp. 2335-2356. https://doi.org/10.1007/s11269-019-02265-0

Long-term modelling of wind speeds using six different heuristic artificial intelligence approaches

Maroufpoor, Saman, Sanikhani, Hadi, Kisi, Ozgur, Deo, Ravinesh C. and Yaseen, Zaher Mundher. 2019. "Long-term modelling of wind speeds using six different heuristic artificial intelligence approaches." International Journal of Climatology. 39 (8), pp. 3543-3557. https://doi.org/10.1002/joc.6037

Development and evaluation of hybrid artificial neural network architectures for modeling spatio-temporal groundwater fluctuations in a complex aquifer system

Roshni, Thendiyath, Jha, Madan K., Deo, Ravinesh C. and Vandana, A.. 2019. "Development and evaluation of hybrid artificial neural network architectures for modeling spatio-temporal groundwater fluctuations in a complex aquifer system." Water Resources Management. 33 (7), pp. 2381-2397. https://doi.org/10.1007/s11269-019-02253-4

An enhanced extreme learning machine model for river flow forecasting: state-of-the-art, practical applications in water resource engineering area and future research direction

Yaseen, Zaher Mundher, Sulaiman, Sadeq Oleiwi, Deo, Ravinesh C. and Chau, Kwok-Wing. 2019. "An enhanced extreme learning machine model for river flow forecasting: state-of-the-art, practical applications in water resource engineering area and future research direction." Journal of Hydrology. 569, pp. 387-408. https://doi.org/10.1016/j.jhydrol.2018.11.069

The influence of structural factors on stormwater runoff retention of extensive green roofs: new evidence from scale-based models and real experiments

Liu, Wen, Feng, Qi, Chen, Weiping, Wei, Wei and Deo, Ravinesh C.. 2019. "The influence of structural factors on stormwater runoff retention of extensive green roofs: new evidence from scale-based models and real experiments." Journal of Hydrology. 569, pp. 230-238. https://doi.org/10.1016/j.jhydrol.2018.11.066

Direct and indirect impacts of ionic components of saline water on irrigated soil chemical and microbial processes

Chen, Lijuan, Li, Changsheng, Feng, Qi, Wei, Yongping, Zhao, Yan, Zhu, Meng and Deo, Ravinesh C.. 2019. "Direct and indirect impacts of ionic components of saline water on irrigated soil chemical and microbial processes." Catena. 172, pp. 581-589. https://doi.org/10.1016/j.catena.2018.09.030

Global solar radiation prediction by ANN integrated with European Centre for medium range weather forecast fields in solar rich cities of Queensland Australia

Ghimire, Sujan, Deo, Ravinesh C., Downs, Nathan J. and Raj, Nawin. 2019. "Global solar radiation prediction by ANN integrated with European Centre for medium range weather forecast fields in solar rich cities of Queensland Australia." Journal of Cleaner Production. 216, pp. 288-310. https://doi.org/10.1016/j.jclepro.2019.01.158

Future projection with an extreme-learning machine and support vector regression of reference evapotranspiration in a mountainous inland watershed in north-west China

Yin, Zhenliang, Feng, Qi, Yang, Linshan, Deo, Ravinesh C., Wen, Xiaohu, Si, Jianhua and Xiao, Shengchun. 2017. "Future projection with an extreme-learning machine and support vector regression of reference evapotranspiration in a mountainous inland watershed in north-west China." Water: an open access journal. 9 (11), pp. 880-902. https://doi.org/10.3390/w9110880

The spatial and temporal contribution of glacier runoff to watershed discharge in the Yarkant River Basin, Northwest China

Yin, Zhenliang, Feng, Qi, Liu, Shiyin, Zhou, Songbing, Li, Jing, Yang, Linshan and Deo, Ravinesh C.. 2017. "The spatial and temporal contribution of glacier runoff to watershed discharge in the Yarkant River Basin, Northwest China." Water: an open access journal. 9 (3), pp. 159-178. https://doi.org/10.3390/w9030159

Particle swarm optimized–support vector regression hybrid model for daily horizon electricity demand forecasting using climate dataset

Al-Musaylh, Mohanad S., Deo, Ravinesh C. and Li, Yan. 2018. "Particle swarm optimized–support vector regression hybrid model for daily horizon electricity demand forecasting using climate dataset." Huang, Q. and Kolhe, M. (ed.) 3rd International Conference on Power and Renewable Energy (ICPRE 2018). Berlin, Germany 21 - 24 Sep 2018 Germany. https://doi.org/10.1051/e3sconf/20186408001

Effects of topography on soil organic carbon stocks in grasslands of a semiarid alpine region, northwestern China

Zhu, Meng, Feng, Qi, Zhang, Mengxu, Liu, Wei, Qin, Yanyan, Deo, Ravinesh C. and Zhang, Chengqi. 2019. "Effects of topography on soil organic carbon stocks in grasslands of a semiarid alpine region, northwestern China." Journal of Soils and Sediments: protection, risk assessment and remediation. 19 (4), pp. 1640-1650. https://doi.org/10.1007/s11368-018-2203-0

A joint deep neural network model for pain recognition from face

Bargshady, Ghazal, Soar, Jeffrey, Zhou, Xujuan, Deo, Ravinesh, Whittaker, Frank and Wang, Hua. 2019. "A joint deep neural network model for pain recognition from face." 4th IEEE International Conference on Computer and Communication Systems (ICCCS 2019). Singapore 23 - 25 Feb 2019 Singapore. pp. 52-56 https://doi.org/10.1109/CCOMS.2019.8821779

Effects of Afforestation on Soil Bulk Density and pH in the Loess Plateau, China

Zhang, Xiaofang, Adamowski, Jan F., Deo, Ravinesh C., Xu, Xueyun, Zhu, Guofeng and Cao, Jianjun. 2018. "Effects of Afforestation on Soil Bulk Density and pH in the Loess Plateau, China." Water: an open access journal. 10 (12), pp. 1-15. https://doi.org/10.3390/w10121710

Assessment of soil salinisation in the Ejina Oasis located in the lower reaches of Heihe River, Northwestern China

Zhao, Yu, Feng, Qi, Lu, Aigang and Deo, Ravinesh C.. 2019. "Assessment of soil salinisation in the Ejina Oasis located in the lower reaches of Heihe River, Northwestern China." Chemistry and Ecology. 35 (4), pp. 330-343. https://doi.org/10.1080/02757540.2018.1554060

Design and implementation of a hybrid MLP-GSA model with multilayer perceptron-gravitational search algorithm for monthly lake water level forecasting

Ghorbani, Mohammad Ali, Deo, Ravinesh C., Karimi, Vahid, Kashani, Mahsa H. and Ghorbani, Shahryar. 2018. "Design and implementation of a hybrid MLP-GSA model with multilayer perceptron-gravitational search algorithm for monthly lake water level forecasting." Stochastic Environmental Research and Risk Assessment. 33 (1), pp. 125-147. https://doi.org/10.1007/s00477-018-1630-1

Monitoring paddy productivity in North Korea employing geostationary satellite images integrated with GRAMI-rice model

Yeom, Jong-min, Jeong, Seungtaek, Jeong, Gwanyong, Ng, Chi Tim, Deo, Ravinesh C. and Ko, Jonghan. 2018. "Monitoring paddy productivity in North Korea employing geostationary satellite images integrated with GRAMI-rice model." Scientific Reports. 8, pp. 1-15. https://doi.org/10.1038/s41598-018-34550-0

Artificial intelligence approach for the prediction of Robusta coffee yield using soil fertility properties

Kouadio, Louis, Deo, Ravinesh C., Byrareddy, Vivekananda, Adamowski, Jan F., Mushtaq, Shahbaz and Nguyen, Van Phuong. 2018. "Artificial intelligence approach for the prediction of Robusta coffee yield using soil fertility properties." Computers and Electronics in Agriculture. 155, pp. 324-338. https://doi.org/10.1016/j.compag.2018.10.014

Artificial intelligence-based fast and efficient hybrid approach for spatial modelling of soil electrical conductivity

Ghorbani, Mohammad Ali, Deo, Ravinesh C., Kashani, Mahsa H., Shahabi, Mahmoud and Ghorbani, Shahryar. 2019. "Artificial intelligence-based fast and efficient hybrid approach for spatial modelling of soil electrical conductivity." Soil and Tillage Research. 186, pp. 152-164. https://doi.org/10.1016/j.still.2018.09.012

Quantifying flood events in Bangladesh with a daily-step flood monitoring index based on the concept of daily effective precipitation

Deo, Ravinesh C., Adamowski, Jan F., Begum, Khaleda, Salcedo-sanz, Sancho, Kim, Do-Woo, Dayal, Kavina S. and Byun, Hi-Ryong. 2019. "Quantifying flood events in Bangladesh with a daily-step flood monitoring index based on the concept of daily effective precipitation." Theoretical and Applied Climatology. 137, pp. 1201-1215. https://doi.org/10.1007/s00704-018-2657-4

Shear strength prediction of steel fiber reinforced concrete beam using hybrid intelligence models: a new approach

Yaseen, Zaheer Munder, Tran, Minh Tung, Kim, Sungwon, Bakhshpoori, Taha and Deo, Ravinesh C.. 2018. "Shear strength prediction of steel fiber reinforced concrete beam using hybrid intelligence models: a new approach." Engineering Structures. 177, pp. 244-255. https://doi.org/10.1016/j.engstruct.2018.09.074

Adaptive Neuro-Fuzzy Inference System integrated with solar zenith angle for forecasting sub-tropical photosynthetically active radiation

Deo, Ravinesh C., Downs, Nathan J., Adamowski, Jan F. and Parisi, Alfio V.. 2018. "Adaptive Neuro-Fuzzy Inference System integrated with solar zenith angle for forecasting sub-tropical photosynthetically active radiation." Food and Energy Security. 8 (1). https://doi.org/10.1002/fes3.151

Cotton yield prediction with Markov Chain Monte Carlo-based simulation model integrated with genetic programing algorithm: a new hybrid copula-driven approach

Ali, Mumtaz, Deo, Ravinesh C., Downs, Nathan J. and Maraseni, Tek. 2018. "Cotton yield prediction with Markov Chain Monte Carlo-based simulation model integrated with genetic programing algorithm: a new hybrid copula-driven approach." Agricultural and Forest Meteorology. 263, pp. 428-448. https://doi.org/10.1016/j.agrformet.2018.09.002

Weekly heat wave death prediction model using zero-inflated regression approach

Kim, Do-Woo, Deo, Ravinesh C., Park, Sang-Jin, Lee, Jong-Seol and Lee, Woo-Seop. 2019. "Weekly heat wave death prediction model using zero-inflated regression approach." Theoretical and Applied Climatology. 137 (1-2), pp. 823-838. https://doi.org/10.1007/s00704-018-2636-9

A comparative study of temperature and precipitation‑based aridity indices and their trends in Mongolia

Nyamtseren, Mandakh, Feng, Qi and Deo, Ravinesh C.. 2018. "A comparative study of temperature and precipitation‑based aridity indices and their trends in Mongolia." International Journal of Environmental Research. 12, pp. 887-899. https://doi.org/10.1007/s41742-018-0143-6

Can individual land ownership reduce grassland degradation and favor socioeconomic sustainability on the Qinghai-Tibetan Plateau?

Cao, J. J., Holden, N. M., Adamowski, J. F., Deo, R. C., Xu, X. Y. and Feng, Q.. 2018. "Can individual land ownership reduce grassland degradation and favor socioeconomic sustainability on the Qinghai-Tibetan Plateau?" Environmental Science and Policy. 89, pp. 192-197. https://doi.org/10.1016/j.envsci.2018.08.003

Copula-based agricultural conditional value-at-risk modelling for geographical diversifications in wheat farming portfolio management

Nguyen-Huy, Thong, Deo, Ravinesh C., Mushtaq, Shahbaz, Kath, Jarrod and Khan, Shahjahan. 2018. "Copula-based agricultural conditional value-at-risk modelling for geographical diversifications in wheat farming portfolio management." Weather and Climate Extremes. 21, pp. 76-89. https://doi.org/10.1016/j.wace.2018.07.002

Design and evaluation of SVR, MARS and M5Tree models for 1, 2 and 3-day lead time forecasting of river flow data in a semiarid mountainous catchment

Yin, Zhenliang, Feng, Qi, Wen, Xiaohu, Deo, Ravinesh C., Yang, Linshan, Si, Jianhua and He, Zhibin. 2018. "Design and evaluation of SVR, MARS and M5Tree models for 1, 2 and 3-day lead time forecasting of river flow data in a semiarid mountainous catchment." Stochastic Environmental Research and Risk Assessment. 32 (9), pp. 2457-2476. https://doi.org/10.1007/s00477-018-1585-2

Mapping hypothermia death vulnerability in Korea

Park, Sang-Jin, Kim, Do-Woo, Deo, Ravinesh C. and Lee, Jong-Seol. 2018. "Mapping hypothermia death vulnerability in Korea." International Journal of Disaster Risk Reduction. 31, pp. 668-678. https://doi.org/10.1016/j.ijdrr.2018.06.016

Multi-stage committee based extreme learning machine model incorporating the influence of climate parameters and seasonality on drought forecasting

Ali, Mumtaz, Deo, Ravinesh C., Downs, Nathan J. and Maraseni, Tek. 2018. "Multi-stage committee based extreme learning machine model incorporating the influence of climate parameters and seasonality on drought forecasting." Computers and Electronics in Agriculture. 152, pp. 149-165. https://doi.org/10.1016/j.compag.2018.07.013

A real-time hourly water index for flood risk monitoring: pilot studies in Brisbane, Australia, and Dobong Observatory, South Korea

Deo, Ravinesh C., Byun, Hi-Ryong, Kim, Ga-Byn and Adamowski, Jan F.. 2018. "A real-time hourly water index for flood risk monitoring: pilot studies in Brisbane, Australia, and Dobong Observatory, South Korea." Environmental Monitoring and Assessment. 190 (450). https://doi.org/10.1007/s10661-018-6806-0

Multi-stage hybridized online sequential extreme learning machine integrated with Markov Chain Monte Carlo copula-Bat algorithm for rainfall forecasting

Ali, Mumtaz, Deo, Ravinesh C., Downs, Nathan J. and Maraseni, Tek. 2018. "Multi-stage hybridized online sequential extreme learning machine integrated with Markov Chain Monte Carlo copula-Bat algorithm for rainfall forecasting." Atmospheric Research. 213, pp. 450-464. https://doi.org/10.1016/j.atmosres.2018.07.005

Influence of stand type and stand age on soil carbon storage in China’s arid and semi-arid regions

Cao, Jianjun, Zhang, Xiaofang, Deo, Ravinesh, Gong, Yifan and Feng, Qi. 2018. "Influence of stand type and stand age on soil carbon storage in China’s arid and semi-arid regions." Land Use Policy: the international journal covering all aspects of land use. 78, pp. 258-265. https://doi.org/10.1016/j.landusepol.2018.07.002

Design and implementation of a hybrid model based on two-layer decomposition method coupled with extreme learning machines to support real-time environmental monitoring of water quality parameters

Fijani, Elham, Barzegar, Rahim, Deo, Ravinesh, Tziritis, Evangelos and Konstantinos, Skordas. 2019. "Design and implementation of a hybrid model based on two-layer decomposition method coupled with extreme learning machines to support real-time environmental monitoring of water quality parameters." Science of the Total Environment. 648, pp. 839-853. https://doi.org/10.1016/j.scitotenv.2018.08.221

Optimization of windspeed prediction using an artificial neural network compared with a genetic programming model

Deo, Ravinesh C., Ghimire, Sujan, Downs, Nathan J. and Raj, Nawin. 2018. "Optimization of windspeed prediction using an artificial neural network compared with a genetic programming model." Kim, Dookie, Roy, Sanjiban Sekhar, Lansivaara, Tim, Deo, Ravinesh C. and Samui, Pijush (ed.) Handbook of research on predictive modeling and optimization methods in science and engineering. Hershey, United States. IGI Global. pp. 328-359

Hybrid data intelligent models and applications for water level prediction

Yaseen, Zaher Mundher, Deo, Ravinesh C., Ebtehaj, Isa and Bonakdari, Hossein. 2018. "Hybrid data intelligent models and applications for water level prediction." Kim, Dookie, Roy, Sanjiban Sekhar, Länsivaara, Tim, Deo, Ravinesh C. and Samui, Pijush (ed.) Handbook of research on predictive modeling and optimization methods in science and engineering. Hershey, United States. IGI Global. pp. 121-139

Selection of representative feature training sets with self-organized maps for optimized time series modeling and prediction: application to forecasting daily drought conditions with ARIMA and neural network models

McCarthy, Elizabeth, Deo, Ravinesh C., Li, Yan and Maraseni, Tek. 2018. "Selection of representative feature training sets with self-organized maps for optimized time series modeling and prediction: application to forecasting daily drought conditions with ARIMA and neural network models." Kim, Dookie, Roy, Sanjiban Sekhar, Lansivaara, Tim, Deo, Ravinesh C. and Samui, Pijush (ed.) Handbook of research on predictive modeling and optimization methods in science and engineering. Hershey, United States. IGI Global. pp. 446-464

Survey of different data-intelligent modeling strategies for forecasting air temperature using geographic information as model predictors

Sanikhani, Hadi, Deo, Ravinesh C., Samui, Pijush, Kisi, Ozgur, Mert, Chian, Mirabbasi, Rasoul, Gavili, Siavash and Yaseen, Zaher Mundher. 2018. "Survey of different data-intelligent modeling strategies for forecasting air temperature using geographic information as model predictors." Computers and Electronics in Agriculture. 152, pp. 242-260. https://doi.org/10.1016/j.compag.2018.07.008

Soil moisture forecasting by a hybrid machine learning technique: ELM integrated with ensemble empirical mode decomposition

Prasad, Ramendra, Deo, Ravinesh C., Li, Yan and Maraseni, Tek. 2018. "Soil moisture forecasting by a hybrid machine learning technique: ELM integrated with ensemble empirical mode decomposition." Geoderma. 330, pp. 136-161. https://doi.org/10.1016/j.geoderma.2018.05.035

Modeling the joint influence of multiple synoptic-scale, climate mode indices on Australian wheat yield using a vine copula-based approach

Nguyen-Huy, Thong, Deo, Ravinesh C., Mushtaq, Shahbaz, An-Vo, Duc-Anh and Khan, Shahjahan. 2018. "Modeling the joint influence of multiple synoptic-scale, climate mode indices on Australian wheat yield using a vine copula-based approach." European Journal of Agronomy. 98, pp. 65-81. https://doi.org/10.1016/j.eja.2018.05.006

Non-tuned data intelligent model for soil temperature estimation: a new approach

Sanikhani, Hadi, Deo, Ravinesh C., Yaseen, Zaher Mundheer, Eray, Okan and Kisi, Ozgur. 2018. "Non-tuned data intelligent model for soil temperature estimation: a new approach." Geoderma. 330, pp. 52-64. https://doi.org/10.1016/j.geoderma.2018.05.030

Drought prediction with standardized precipitation and evapotranspiration index and support vector regression models

Deo, Ravinesh C., Salcedo-sanz, Sancho, Carro-Calvo, Leopoldo and Saavedra-Moreno, Beatriz. 2018. "Drought prediction with standardized precipitation and evapotranspiration index and support vector regression models." Samui, Pijush, Kim, Dookie and Ghosh, Chandan (ed.) Integrating disaster science and management. Amsterdam, Netherlands. Elsevier. pp. 151-174

Drought modelling based on artificial intelligence and neural network algorithms: a case study in Queensland, Australia

Dayal, Kavina, Deo, Ravinesh and Apan, Armando A.. 2017. "Drought modelling based on artificial intelligence and neural network algorithms: a case study in Queensland, Australia." Filho, Walter Leal (ed.) Climate change adaptation in Pacific countries:fostering resilience and improving the quality of life. Springer. pp. 177-198

Input selection and data-driven model performance optimization to predict the Standardized Precipitation and Evaporation Index in a drought-prone region

Mouatadid, Soukayna, Raj, Nawin, Deo, Ravinesh C. and Adamowski, Jan F.. 2018. "Input selection and data-driven model performance optimization to predict the Standardized Precipitation and Evaporation Index in a drought-prone region." Atmospheric Research. 212, pp. 130-149. https://doi.org/10.1016/j.atmosres.2018.05.012

Self-adaptive differential evolutionary extreme learning machines for long-term solar radiation prediction with remotely-sensed MODIS satellite and Reanalysis atmospheric products in solar-rich cities

Ghimire, Sujan, Deo, Ravinesh C., Downs, Nathan J. and Raj, Nawin. 2018. "Self-adaptive differential evolutionary extreme learning machines for long-term solar radiation prediction with remotely-sensed MODIS satellite and Reanalysis atmospheric products in solar-rich cities." Remote Sensing of Environment: an interdisciplinary journal. 212, pp. 176-198. https://doi.org/10.1016/j.rse.2018.05.003

An ensemble-ANFIS based uncertainty assessment model for forecasting multi-scalar standardized precipitation index

Ali, Mumtaz, Deo, Ravinesh C., Downs, Nathan J. and Maraseni, Tek. 2018. "An ensemble-ANFIS based uncertainty assessment model for forecasting multi-scalar standardized precipitation index." Atmospheric Research. 207, pp. 155-180. https://doi.org/10.1016/j.atmosres.2018.02.024

Wavelet analysis–artificial neural network conjunction models for multi-scale monthly groundwater level predicting in an arid inland river basin, northwestern China

Wen, Xiaohu, Feng, Qi, Deo, Ravinesh C., Wu, Min and Si, Jianhua. 2017. "Wavelet analysis–artificial neural network conjunction models for multi-scale monthly groundwater level predicting in an arid inland river basin, northwestern China." Hydrology Research: an international journal. 48 (6), pp. 1710-1729. https://doi.org/10.2166/nh.2016.396

Ensemble committee-based data intelligent approach for generating soil moisture forecasts with multivariate hydro-meteorological predictors

Prasad, Ramendra, Deo, Ravinesh C., Li, Yan and Maraseni, Tek. 2018. "Ensemble committee-based data intelligent approach for generating soil moisture forecasts with multivariate hydro-meteorological predictors." Soil and Tillage Research. 181, pp. 63-81. https://doi.org/10.1016/j.still.2018.03.021

Comparison of social-ecological resilience between two grassland management patterns driven by grassland land contract policy in the Maqu, Qinghai-Tibetan Plateau

Cao, Jianjun, Li, Mengtian, Deo, Ravinesh C., Adamowski, Jan F, Cerda, Artemi, Feng, Qi, Liu, Minxia, Zhang, Jian, Zhu, Guofeng, Zhang, Xuebin, Xu, Xueyun, Yang, Shurong and Gong, Yifan. 2018. "Comparison of social-ecological resilience between two grassland management patterns driven by grassland land contract policy in the Maqu, Qinghai-Tibetan Plateau." Land Use Policy: the international journal covering all aspects of land use. 74, pp. 88-96. https://doi.org/10.1016/j.landusepol.2017.07.027

Spatio-temporal drought risk mapping approach and its application in the drought-prone region of south-east Queensland, Australia

Dayal, Kavina S., Deo, Ravinesh C. and Apan, Armando A.. 2018. "Spatio-temporal drought risk mapping approach and its application in the drought-prone region of south-east Queensland, Australia." Natural Hazards. 93 (2), pp. 823-847. https://doi.org/10.1007/s11069-018-3326-8

A new approach to predict daily pH in rivers based on the 'a trous' redundant wavelet transform algorithm

Rajaee, Taher, Ravansalar, Masoud, Adamowski, Jan F. and Deo, Ravinesh C.. 2018. "A new approach to predict daily pH in rivers based on the 'a trous' redundant wavelet transform algorithm." Water, Air and Soil Pollution: an international journal of environmental pollution. 229 (3). https://doi.org/10.1007/s11270-018-3715-3

Computational intelligence approaches for energy load forecasting in smart energy management grids: state of the art, future challenges, and research directions and Research Directions

Fallah, Seyedeh Narjes, Deo, Ravinesh Chand, Shojafar, Mohammad, Conti, Mauro and Shamshirband, Shahaboddin. 2018. "Computational intelligence approaches for energy load forecasting in smart energy management grids: state of the art, future challenges, and research directions and Research Directions." Energies. 11 (3). https://doi.org/10.3390/en11030596

Two-phase particle swarm optimized-support vector regression hybrid model integrated with improved empirical mode decomposition with adaptive noise for multiple-horizon electricity demand forecasting

Al-Musaylh, Mohanad S., Deo, Ravinesh C., Li, Yan and Adamowski, Jan F.. 2018. "Two-phase particle swarm optimized-support vector regression hybrid model integrated with improved empirical mode decomposition with adaptive noise for multiple-horizon electricity demand forecasting." Applied Energy. 217, pp. 422-439. https://doi.org/10.1016/j.apenergy.2018.02.140

Application of the hybrid artificial neural network coupled with rolling mechanism and grey model algorithms for streamflow forecasting over multiple time horizons

Yaseen, Zaher Mundher, Fu, Minglei, Wang, Chen, Mohtar, Wan Hanna Melini Wan, Deo, Ravinesh C. and El-Shafie, Ahmed. 2018. "Application of the hybrid artificial neural network coupled with rolling mechanism and grey model algorithms for streamflow forecasting over multiple time horizons." Water Resources Management. 32 (5), pp. 1883-1899. https://doi.org/10.1007/s11269-018-1909-5

Multi-household grazing management pattern maintains better soil fertility

Cao, Jianjun, Xu, Xueyun, Deo, Ravinesh C., Holden, Nicholas M., Adamowski, Jan F., Gong, Yifan, Feng, Qi, Yang, Shurong, Li, Mengtian, Zhou, Junju, Zhang, Jian and Liu, Minxia. 2018. "Multi-household grazing management pattern maintains better soil fertility." Agronomy for Sustainable Development: sciences des productions vegetales et de l'environnement. 38 (1). https://doi.org/10.1007/s13593-017-0482-2

Short-term electricity demand forecasting with MARS, SVR and ARIMA models using aggregated demand data in Queensland, Australia

Al-Musaylh, Mohanad S., Deo, Ravinesh C., Adamowski, Jan F. and Li, Yan. 2018. "Short-term electricity demand forecasting with MARS, SVR and ARIMA models using aggregated demand data in Queensland, Australia." Advanced Engineering Informatics: the science of supporting knowledge-intensive activities. 35 (C), pp. 1-16. https://doi.org/10.1016/j.aei.2017.11.002

Mapping groundwater contamination risk of multiple aquifers using multi-model ensemble of machine learning algorithms

Barzegar, Rahim, Moghaddam, Asghar Asghari, Deo, Ravinesh, Fijani, Elham and Tziritis, Evangelos. 2018. "Mapping groundwater contamination risk of multiple aquifers using multi-model ensemble of machine learning algorithms." Science of the Total Environment. 621, pp. 697-712. https://doi.org/10.1016/j.scitotenv.2017.11.185

Investigating drought duration-severity-intensity characteristics using the Standardized Precipitation-Evapotranspiration Index: case studies in drought-prone Southeast Queensland

Dayal, Kavina S., Deo, Ravinesh C. and Apan, Armando A.. 2018. "Investigating drought duration-severity-intensity characteristics using the Standardized Precipitation-Evapotranspiration Index: case studies in drought-prone Southeast Queensland." Journal of Hydrologic Engineering. 23 (1), p. 05017029. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001593

An efficient neuro-evolutionary hybrid modelling mechanism for the estimation of daily global solar radiation in the Sunshine State of Australia

Salcedo-sanz, Sancho, Deo, Ravinesh C., Cornejo-Bueno, Laura, Camacho-Gomez, Carlos and Ghimire, Sujan. 2018. "An efficient neuro-evolutionary hybrid modelling mechanism for the estimation of daily global solar radiation in the Sunshine State of Australia." Applied Energy. 209, pp. 79-94. https://doi.org/10.1016/j.apenergy.2017.10.076

Multi-layer perceptron hybrid model integrated with the firefly optimizer algorithm for windspeed prediction of target site using a limited set of neighboring reference station data

Deo, Ravinesh C., Ghorbani, Mohammad Ali, Samadianfard, Saeed, Maraseni, Tek, Bilgili, Mehmet and Biazar, Mustafa. 2018. "Multi-layer perceptron hybrid model integrated with the firefly optimizer algorithm for windspeed prediction of target site using a limited set of neighboring reference station data." Renewable Energy. 116 (Part A), pp. 309-323. https://doi.org/10.1016/j.renene.2017.09.078

Identifying separate impacts of climate and land use/cover change on hydrological processes in upper stream of Heihe River, northwest China

Yang, Linshan, Feng, Qi, Yin, Zhenliang, Wen, Xiaohu, Si, Jianhua, Li, Changbin and Deo, Ravinesh C.. 2017. "Identifying separate impacts of climate and land use/cover change on hydrological processes in upper stream of Heihe River, northwest China." Hydrological Processes. 31 (5), pp. 1100-1112. https://doi.org/10.1002/hyp.11098

Reservoir inflow forecasting with a modified coactive neuro-fuzzy inference system: a case study for a semi-arid region

Allawi, Mohammed Falah, Jaafar, Othman, Hamzah, Firdaus Mohamad, Mohd, Nuruol Syuhadaa, Deo, Ravinesh C. and El-Shafie, Ahmed. 2018. "Reservoir inflow forecasting with a modified coactive neuro-fuzzy inference system: a case study for a semi-arid region." Theoretical and Applied Climatology. 134 (1-2), pp. 545-563. https://doi.org/10.1007/s00704-017-2292-5

Implementation of a hybrid MLP-FFA model for water level prediction of Lake Egirdir, Turkey

Ghorbani, Mohammad Ali, Deo, Ravinesh C., Karimi, Vahid, Yaseen, Zaher Mundher and Terz, Ozlem. 2018. "Implementation of a hybrid MLP-FFA model for water level prediction of Lake Egirdir, Turkey." Stochastic Environmental Research and Risk Assessment. 32 (6), pp. 1683-1697. https://doi.org/10.1007/s00477-017-1474-0

Pan evaporation prediction using a hybrid multilayer perceptron-firefly algorithm (MLP-FFA) model: case study in North Iran

Ghorbani, M. A., Deo, Ravinesh C., Yaseen, Zaher Mundher, Kashani, Mahsa H. and Mohammadi, Babak. 2018. "Pan evaporation prediction using a hybrid multilayer perceptron-firefly algorithm (MLP-FFA) model: case study in North Iran." Theoretical and Applied Climatology. 133 (3-4), pp. 1119-1131. https://doi.org/10.1007/s00704-017-2244-0

Impact of grassland contract policy on soil organic carbon losses from alpine grassland on the Qinghai–Tibetan Plateau

Cao, J., Gong, Y., Yeh, E. T., Holden, N. M., Adamowski, J. F., Deo, R. C., Liu, M., Zhou, J., Zhang, J., Zhang, S., Sheng, D., Yang, S., Xu, X., Li, M. and Feng, Q.. 2017. "Impact of grassland contract policy on soil organic carbon losses from alpine grassland on the Qinghai–Tibetan Plateau." Soil Use and Management. 33 (4), pp. 633-671. https://doi.org/10.1111/sum.12387

Effects of ecological water transport on photosynthesis and chlorophyll fluorescence of Populus euphratica

Zhao, Chun Yan, Si, Jian Hua, Feng, Qi, Yu, Teng Fei, Deo, Ravinesh C. and Luo, Huan. 2018. "Effects of ecological water transport on photosynthesis and chlorophyll fluorescence of Populus euphratica." Water Science and Technology: Water Supply. 18 (5), pp. 1747-1756. https://doi.org/10.2166/ws.2017.236

Trend analysis of Water Poverty Index for assessment of water stress and water management polices: a case study in the Hexi Corridor, China

Huang, Shan, Feng, Qi, Lu, Zhixiang, Wen, Xiaohu and Deo, Ravinesh C.. 2017. "Trend analysis of Water Poverty Index for assessment of water stress and water management polices: a case study in the Hexi Corridor, China." Sustainability. 9 (5), pp. 756-772. https://doi.org/10.3390/su9050756

Forecasting evaporative loss by least-square support-vector regression and evaluation with genetic programming, Gaussian process, and minimax probability machine regression: case study of Brisbane City

Deo, Ravinesh C. and Samui, Pijush. 2017. "Forecasting evaporative loss by least-square support-vector regression and evaluation with genetic programming, Gaussian process, and minimax probability machine regression: case study of Brisbane City." Journal of Hydrologic Engineering. 22 (6), pp. 1-15. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001506

Statistical evaluation of rainfall time series in concurrence with agriculture and water resources of Ken River basin, Central India (1901–2010)

Meshram, Sarita Gajbhiye, Singh, Sudhir Kumar, Meshram, Chandrashekhar, Deo, Ravinesh C. and Ambade, Balram. 2018. "Statistical evaluation of rainfall time series in concurrence with agriculture and water resources of Ken River basin, Central India (1901–2010)." Theoretical and Applied Climatology. 134, pp. 1231-1243. https://doi.org/10.1007/s00704-017-2335-y

An international comparison of rice consumption behaviours and greenhouse gas emissions from rice production

Maraseni, Tek Narayan, Deo, Ravinesh C., Qu, Jiansheng, Gentle, Popular and Neupane, Prem Raj. 2018. "An international comparison of rice consumption behaviours and greenhouse gas emissions from rice production." Journal of Cleaner Production. 172, pp. 2288-2300. https://doi.org/10.1016/j.jclepro.2017.11.182

Physiological response to salinity stress and tolerance mechanics of Populus euphratica

Zhao, Chun Yan, Si, Jian Hua, Feng, Qi, Deo, Ravinesh C., Yu, Teng Fei and Li, Pei Du. 2017. "Physiological response to salinity stress and tolerance mechanics of Populus euphratica." Environmental Monitoring and Assessment. 189 (11), pp. 533-543. https://doi.org/10.1007/s10661-017-6257-z

Carbon dioxide fluxes and their environmental controls in a riparian forest within the hyper-arid region of Northwest China

Ma, Xiaohong, Feng, Qi, Yu, Tengfei, Su, Yonghong and Deo, Ravinesh C.. 2017. "Carbon dioxide fluxes and their environmental controls in a riparian forest within the hyper-arid region of Northwest China." Forests. 8 (10), pp. 1-17. https://doi.org/10.3390/f8100379

Comparative study of hybrid-wavelet artificial intelligence models for monthly groundwater depth forecasting in extreme arid regions, Northwest China

Yu, Haijiao, Wen, Xiaohu, Feng, Qi, Deo, Ravinesh C., Si, Jianhua and Wu, Min. 2018. "Comparative study of hybrid-wavelet artificial intelligence models for monthly groundwater depth forecasting in extreme arid regions, Northwest China." Water Resources Management. 32 (1), pp. 301-323. https://doi.org/10.1007/s11269-017-1811-6

Predicting compressive strength of lightweight foamed concrete using extreme learning machine model

Yaseen, Zaher Mundher, Deo, Ravinesh C., Hilal, Ameer, Abd, Abbas M., Bueno, Laura Cornejo, Salcedo-sanz, Sancho and Nehdi, Moncef L.. 2018. "Predicting compressive strength of lightweight foamed concrete using extreme learning machine model." Advances in Engineering Software. 115, pp. 112-125. https://doi.org/10.1016/j.advengsoft.2017.09.004

Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model

Yaseen, Zaher Mundher, Ebtehaj, Isa, Bonakdari, Hossein, Deo, Ravinesh C., Mehr, Ali Danandeh, Mohtar, Wan Hanna Melini Wan, Diop, Lamine, El-Shafie, Ahmed and Singh, Vijay P.. 2017. "Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model." Journal of Hydrology. 554, pp. 263-276. https://doi.org/10.1016/j.jhydrol.2017.09.007

Rainfall Pattern Forecasting Using Novel Hybrid Intelligent Model Based ANFIS-FFA

Yaseen, Zaher Mundher, Ghareb, Mazen Ismaeel, Ebtehaj, Isa, Bonakdari, Hossein, Siddique, Ridwan, Heddam, Sali, Yusif, Ali A. and Deo, Ravinesh. 2018. "Rainfall Pattern Forecasting Using Novel Hybrid Intelligent Model Based ANFIS-FFA." Water Resources Management. 32 (1), pp. 105-122. https://doi.org/10.1007/s11269-017-1797-0

Synthetic retrieval of hourly net ecosystem exchange using the neural network model with combined MI and GOCI geostationary sensor datasets and ground-based measurements

Yeom, Jong-Min, Deo, Ravinesh, Chun, Junghwa, Hong, Jinkyu, Kim, Dong-Su, Han, Kyung-Soo and Cho, Jaeil. 2017. "Synthetic retrieval of hourly net ecosystem exchange using the neural network model with combined MI and GOCI geostationary sensor datasets and ground-based measurements." International Journal of Remote Sensing. 38 (23), pp. 7441-7456. https://doi.org/10.1080/01431161.2017.1375573

Separation of the Climatic and Land Cover Impacts on the Flow Regime Changes in Two Watersheds of Northeastern Tibetan Plateau

Yang, Linshan, Feng, Qi, Yin, Zhenliang, Deo, Ravinesh C., Wen, Xiaohu, Si, Jianhua and Li, Changbin. 2017. "Separation of the Climatic and Land Cover Impacts on the Flow Regime Changes in Two Watersheds of Northeastern Tibetan Plateau." Advances in Meteorology. 2017, pp. 1-15. https://doi.org/10.1155/2017/6310401

Changes in climatic elements in the Pan-Hexi region during 1960–2014 and responses to global climatic changes

Wei, Liu, Feng, Qi and Deo, Ravinesh C.. 2018. "Changes in climatic elements in the Pan-Hexi region during 1960–2014 and responses to global climatic changes." Theoretical and Applied Climatology. 133 (1-2), pp. 405-420. https://doi.org/10.1007/s00704-017-2194-6

Mapping heatwave vulnerability in Korea

Kim, Do-Woo, Deo, Ravinesh C., Lee, Jong-Seol and Yeom, Jong-Min. 2017. "Mapping heatwave vulnerability in Korea." Natural Hazards. 89 (1), pp. 35-55. https://doi.org/10.1007/s11069-017-2951-y

Copula-statistical precipitation forecasting model in Australia’s agro-ecological zones

Nguyen-Huy, Thong, Deo, Ravinesh C., An-Vo, Duc-Anh, Mushtaq, Shahbaz and Khan, Shahjahan. 2017. "Copula-statistical precipitation forecasting model in Australia’s agro-ecological zones." Agricultural Water Management. 191, pp. 153-172. https://doi.org/10.1016/j.agwat.2017.06.010

Input selection and performance optimization of ANN-based streamflow forecasts in the drought-prone Murray Darling Basin region using IIS and MODWT algorithm

Prasad, Ramendra, Deo, Ravinesh C., Li, Yan and Maraseni, Tek. 2017. "Input selection and performance optimization of ANN-based streamflow forecasts in the drought-prone Murray Darling Basin region using IIS and MODWT algorithm." Atmospheric Research. 197, pp. 42-63. https://doi.org/10.1016/j.atmosres.2017.06.014

Very short-term reactive forecasting of the solar ultraviolet index using an extreme learning machine integrated with the solar zenith angle

Deo, Ravinesh C., Downs, Nathan, Parisi, Alfio V., Adamowski, Jan F. and Quilty, John M.. 2017. "Very short-term reactive forecasting of the solar ultraviolet index using an extreme learning machine integrated with the solar zenith angle." Environmental Research. 155, pp. 141-166. https://doi.org/10.1016/j.envres.2017.01.035

Association between plant species diversity and edaphic factors in the lower reaches of the Heihe River, northwestern China

Zhao, Yu, Feng, Qi, Xi, Haiyang, Li, Huiya, Yang, Huaide and Deo, Ravinesh C.. 2017. "Association between plant species diversity and edaphic factors in the lower reaches of the Heihe River, northwestern China." Chemistry and Ecology. 33 (3), pp. 181-195. https://doi.org/10.1080/02757540.2017.1287904

Forecasting long-term global solar radiation with an ANN algorithm coupled with satellite-derived (MODIS) land surface temperature (LST) for regional locations in Queensland

Deo, Ravinesh C. and Sahin, Mehmet. 2017. "Forecasting long-term global solar radiation with an ANN algorithm coupled with satellite-derived (MODIS) land surface temperature (LST) for regional locations in Queensland." Renewable and Sustainable Energy Reviews. 72, pp. 828-848. https://doi.org/10.1016/j.rser.2017.01.114

Computational intelligence approach for modeling hydrogen production: a review

Faizollahzadeh, Sina, Najafi, Bahman, Shamshirband, Shahaboddin, Bidgoli, Behrouz Minaei, Deo, Ravinesh Chand and Chau, Kwok-wing. 2018. "Computational intelligence approach for modeling hydrogen production: a review." Engineering Applications of Computational Fluid Mechanics. 12 (1), pp. 438-458. https://doi.org/10.1080/19942060.2018.1452296

Big data in engineering applications

Roy, Sanjiban Sekhar, Samui, Pijushi, Deo, Ravinesh and Ntalampiras, Stalampiras (ed.) 2018. Big data in engineering applications. Singapore. Springer.

Handbook of research on predictive modeling and optimization methods in science and engineering

Kim, Dookie, Roy, Sanjiban Sekhar, Lansivaara, Tim, Deo, Ravinesh C. and Samui, Pijush (ed.) 2018. Handbook of research on predictive modeling and optimization methods in science and engineering. United States. IGI Global.

Re-imagining standard timescales in forecasting precipitation events for Queensland’s grazing enterprises

McCarthy, E., Deo, R. C., Li, Y. and Maraseni, T.. 2017. "Re-imagining standard timescales in forecasting precipitation events for Queensland’s grazing enterprises." Syme, G., Hatton MacDonald, D., Fulton, B. and Piantadosi, J. (ed.) 22nd International Congress on Modelling and Simulation (MODSIM2017). Hobart, Australia 03 - 08 Dec 2017 Australia. Modelling and Simulation Society of Australia and New Zealand . https://doi.org/10.36334/modsim.2017.L1.mccarthy

Stream-flow forecasting using extreme learning machines: a case study in a semi-arid region in Iraq

Yaseen, Zaher Mundher, Jaafar, Othman, Deo, Ravinesh C., Kisi, Ozgur, Adamowski, Jan, Quilty, John and El-Shafie, Ahmed. 2016. "Stream-flow forecasting using extreme learning machines: a case study in a semi-arid region in Iraq." Journal of Hydrology. 542, pp. 603-614. https://doi.org/10.1016/j.jhydrol.2016.09.035

Quantitative definition and spatiotemporal distribution of little water season (LIWAS) in Korea

Kim, Su-Jeong, Byun, Hi-Ryong and Deo, Ravinesh C.. 2016. "Quantitative definition and spatiotemporal distribution of little water season (LIWAS) in Korea." Asia-Pacific Journal of Atmospheric Sciences. 52 (4), pp. 379-393. https://doi.org/10.1007/s13143-016-0012-1

An extreme learning machine model for the simulation of monthly mean streamflow water level in eastern Queensland

Deo, Ravinesh C. and Sahin, Mehmet. 2016. "An extreme learning machine model for the simulation of monthly mean streamflow water level in eastern Queensland." Environmental Monitoring and Assessment. 188 (90). https://doi.org/10.1007/s10661-016-5094-9

Forecasting effective drought index using a wavelet extreme learning machine (W-ELM) model

Deo, Ravinesh C., Tiwari, Mukesh K., Adamowski, Jan F. and Quilty, John M.. 2017. "Forecasting effective drought index using a wavelet extreme learning machine (W-ELM) model." Stochastic Environmental Research and Risk Assessment. 31 (5), pp. 1211-1240. https://doi.org/10.1007/s00477-016-1265-z

Drought forecasting in eastern Australia using multivariate adaptive regression spline, least square support vector machine and M5Tree model

Deo, Ravinesh C., Kisi, Ogzur and Singh, Vijay P.. 2017. "Drought forecasting in eastern Australia using multivariate adaptive regression spline, least square support vector machine and M5Tree model." Atmospheric Research. 184, pp. 149-175. https://doi.org/10.1016/j.atmosres.2016.10.004

A wavelet-coupled support vector machine model for forecasting global incident solar radiation using limited meteorological dataset

Deo, Ravinesh C., Wen, Xiaohu and Feng, Qi. 2016. "A wavelet-coupled support vector machine model for forecasting global incident solar radiation using limited meteorological dataset." Applied Energy. 168, pp. 568-593. https://doi.org/10.1016/j.apenergy.2016.01.130

Application of hybrid artificial neural network algorithm for the prediction of Standardized Precipitation Index

Dayal, Kavina S., Deo, Ravinesh C. and Apan, Armando A.. 2016. "Application of hybrid artificial neural network algorithm for the prediction of Standardized Precipitation Index." 2016 IEEE Region 10 International Conference: Technologies for Smart Nation (TENCON 2016). Singapore 22 - 25 Nov 2016 Singapore. https://doi.org/10.1109/TENCON.2016.7848588

Prediction of SPEI using MLR and ANN: a case study for Wilsons Promontory Station in Victoria

Mouatadid, Soukayna, Deo, Ravinesh C. and Adamowski, Jan F.. 2015. "Prediction of SPEI using MLR and ANN: a case study for Wilsons Promontory Station in Victoria." Guerrero, Juan E. (ed.) 2015 IEEE 14th International Conference on Machine Learning and Applications. Miami, United States of America 09 - 11 Dec 2015 United States. https://doi.org/10.1109/ICMLA.2015.87

Statistical downscaling of climate change scenarios of rainfall and temperature over Indira Sagar Canal Command area in Madhya Pradesh, India

Shukla, Rituraj, Deo, Ravinesh and Khare, Deepak. 2015. "Statistical downscaling of climate change scenarios of rainfall and temperature over Indira Sagar Canal Command area in Madhya Pradesh, India." Guerrero, Juan E. (ed.) 2015 IEEE 14th International Conference on Machine Learning and Applications. Miami, United States of America 09 - 11 Dec 2015 USA. https://doi.org/10.1109/ICMLA.2015.75

Monthly prediction of air temperature in Australia and New Zealand with machine learning algorithms

Salcedo-sanz, S., Deo, R. C., Carro-Calvo, L. and Saavedra-Moreno, B.. 2016. "Monthly prediction of air temperature in Australia and New Zealand with machine learning algorithms." Theoretical and Applied Climatology. 125 (1-2), pp. 13-25. https://doi.org/10.1007/s00704-015-1480-4

Projection of heat wave mortality related to climate change in Korea

Kim, Do-Woo, Deo, Ravinesh C., Chung, Jea-Hak and Lee, Jong-Seol. 2016. "Projection of heat wave mortality related to climate change in Korea." Natural Hazards. 80 (1), pp. 623-637. https://doi.org/10.1007/s11069-015-1987-0

Estimation of monthly evaporative loss using relevance vector machine, extreme learning machine and multivariate adaptive regression spline models

Deo, Ravinesh C., Samui, Pijush and Kim, Dookie. 2016. "Estimation of monthly evaporative loss using relevance vector machine, extreme learning machine and multivariate adaptive regression spline models." Stochastic Environmental Research and Risk Assessment. 30 (6), pp. 1769-1784. https://doi.org/10.1007/s00477-015-1153-y

Numerical modelling of the velocity field of a plane jet flow at moderate jet exit Reynolds numbers

Mossad, Ruth and Deo, Ravinesh C.. 2015. "Numerical modelling of the velocity field of a plane jet flow at moderate jet exit Reynolds numbers." Solnordal, C. B., Liovic, P., Delaney, G. W., Cummins, S. J., Schwarz, M. P. and Witt, P. J. (ed.) 11th International Conference on CFD in the Minerals and Process Industries. Melbourne, Australia 07 - 09 Dec 2015 Melbourne, Australia.

On the new concept of the available water climatology and its application

Byun, H. R., Kim, D. W., Choi, K. S., Deo, R. C., Lee, S. M., Park, C. K., Kwon, S. H., Kim, G. B. and Kwon, H. N.. 2014. "On the new concept of the available water climatology and its application." American Geophysical Union, Fall Meeting 2014. San Francisco, United States 15 - 19 Dec 2014 San Francisco, USA.

A real-time flood monitoring index based on daily effective precipitation and its application to Brisbane and Lockyer Valley flood events

Deo, Ravinesh C., Byun, Hi-Ryong, Adamowski, Jan F. and Kim, Do-Woo. 2015. "A real-time flood monitoring index based on daily effective precipitation and its application to Brisbane and Lockyer Valley flood events." Water Resources Management. 29 (11), pp. 4075-4093. https://doi.org/10.1007/s11269-015-1046-3

Application of the artificial neural network model for prediction of monthly standardized precipitation and evapotranspiration index using hydrometeorological parameters and climate indices in eastern Australia

Deo, Ravinesh C. and Sahin, Mehmet. 2015. "Application of the artificial neural network model for prediction of monthly standardized precipitation and evapotranspiration index using hydrometeorological parameters and climate indices in eastern Australia." Atmospheric Research. 161-162, pp. 65-81. https://doi.org/10.1016/j.atmosres.2015.03.018

Diagnosis of flood events in Brisbane (Australia) using a flood index based on daily effective precipitation

Deo, R. C., Byun, H. R., Adamowski, J. F. and Kim, D. W.. 2014. "Diagnosis of flood events in Brisbane (Australia) using a flood index based on daily effective precipitation." International Conference on Analysis and Management of Changing Risks for Natural Hazards (2014). Padua, Italy Padua, Italy.

Application of the extreme learning machine algorithm for the prediction of monthly Effective Drought Index in eastern Australia

Deo, Ravinesh C. and Sahin, Mehmet. 2015. "Application of the extreme learning machine algorithm for the prediction of monthly Effective Drought Index in eastern Australia." Atmospheric Research. 153, pp. 512-525. https://doi.org/10.1016/j.atmosres.2014.10.016

Drought prediction till 2100 under RCP 8.5 climate change scenarios for Korea

Park, Chang-Kyun, Byun, Hi-Ryong, Deo, Ravinesh and Lee, Bo-Ra. 2015. "Drought prediction till 2100 under RCP 8.5 climate change scenarios for Korea." Journal of Hydrology. 526, pp. 221-230. https://doi.org/10.1016/j.jhydrol.2014.10.043

Influence of sidewalls on the centerline small-scale turbulence of a turbulent high-aspect-ratio rectangular jet

Liu, Y., Zhang, J., Deo, R., Mi, J., Nathan, G. J. and Zhu, R.. 2014. "Influence of sidewalls on the centerline small-scale turbulence of a turbulent high-aspect-ratio rectangular jet." Experimental Thermal and Fluid Science. 58, pp. 139-144. https://doi.org/10.1016/j.expthermflusci.2014.06.021

Comparative analysis of turbulent plane jets from a sharp-edged orifice, a beveled-edge orifice and a radially contoured nozzle

Deo, Ravinesh C.. 2013. "Comparative analysis of turbulent plane jets from a sharp-edged orifice, a beveled-edge orifice and a radially contoured nozzle." International Journal of Mechanical, Industrial Science and Engineering. 7 (12), pp. 1471-1480.

The role of nozzle-exit conditions on the flow field of a plane jet

Deo, Ravinesh C.. 2013. "The role of nozzle-exit conditions on the flow field of a plane jet." International Journal of Mechanical, Industrial Science and Engineering. 7 (12), pp. 1059-1069.

Modelling impacts of vegetation cover change on regional climate

McAlpine, Clive A., Syktus, Jozef I., Deo, Ravinesh C., Lawrence, Peter J., McGowan, Hamish A., Watterson, Ian G. and Phinn, Stuart R.. 2009. Modelling impacts of vegetation cover change on regional climate. Canberra, Australia. Land and Water Australia.

Similarity analysis of the momentum field of a subsonic, plane air jet with varying jet-exit and local Reynolds numbers

Deo, Ravinesh C., Nathan, Graham J. and Mi, Jianchun. 2013. "Similarity analysis of the momentum field of a subsonic, plane air jet with varying jet-exit and local Reynolds numbers." Physics of Fluids. 25 (1). https://doi.org/10.1063/1.4776782

On meteorological droughts in tropical Pacific Islands: time-series analysis of observed rainfall using Fiji as a case study

Deo, Ravinesh C.. 2011. "On meteorological droughts in tropical Pacific Islands: time-series analysis of observed rainfall using Fiji as a case study." Meteorological Applications. 18 (2), pp. 171-180. https://doi.org/10.1002/met.216

Dynamics of precipitation climatology of the Southwest Pacific Region

Deo, Ravinesh Chand. 2001. Dynamics of precipitation climatology of the Southwest Pacific Region. Masters Thesis Master of Science (Research). University of Canterbury, New Zealand.

Climatology of tropical cyclones in the South Pacific Region and their relationships to El Niño events

Deo, Ravinesh C.. 2004. "Climatology of tropical cyclones in the South Pacific Region and their relationships to El Niño events." 16th Australia New Zealand Climate Forum: Climate and Water (ANZCF2004). Lorne, Australia 08 - 10 Nov 2004 Lorne, Vic, Australia.

Designing an evaluation of a tertiary preparatory program within the university context

Deo, Ravinesh. 2011. "Designing an evaluation of a tertiary preparatory program within the university context." PAMA 2011: Global Educators for Contemporary Learning Communities. Toowoomba, Australia 30 May - 10 Jun 2011 Toowoomba, Australia.

Modeling the impact of historical land cover change on Australia's regional climate

McAlpine, C. A., Syktus, J., Deo, R. C., Lawrence, P. J., McGowan, H. A., Watterson, I. G. and Phinn, Stuart. 2007. "Modeling the impact of historical land cover change on Australia's regional climate." Geophysical Research Letters. 34 (22), pp. L22711-1. https://doi.org/10.1029/2007GL031524

Impacts of land use/land cover change on climate and future research priorities

Mahmood, Rezaul, Pielke, Roger A., Hubbard, Kenneth G., Niyogi, Dev, Bonan, Gordon, Lawrence, Peter, McNider, Richard, McAlpine, Clive, Etter, Andres, Gameda, Samuel, Qian, Budong, Carleton, Andrew, Beltran-Przekurat, Adriana, Chase, Thomas, Quintanar, Arturo I., Adegoke, Jimmy O., Vezhapparambu, Sajith, Conner, Glen, Asefi, Salvi, ..., Syktus, Jozef. 2010. "Impacts of land use/land cover change on climate and future research priorities." Bulletin of the American Meteorological Society. 91 (1), pp. 37-46. https://doi.org/10.1175/2009BAMS2769.1

On the influence of initial conditions on a turbulent plane jet: the role of nozzle exit area

Deo, Ravinesh C., Nathan, Graham Jerold and Mi, Jianchun. 2010. "On the influence of initial conditions on a turbulent plane jet: the role of nozzle exit area." Mallinson, G. D. and Cater, J. E. (ed.) 17th Australasian Fluid Mechanics Conference (AFMC 2010). Auckland, New Zealand 05 - 09 Dec 2010 Auckland, New Zealand.

Links between native forest and climate in Australia

Deo, Ravinesh C.. 2011. "Links between native forest and climate in Australia." Weather. 66 (3), pp. 64-69. https://doi.org/10.1002/wea.659

The simulated impact of land cover change on climate extremes in eastern Australia

Deo, R. C., Syktus, J. I., McAlpine, C. A. and Wong, K. K.. 2009. "The simulated impact of land cover change on climate extremes in eastern Australia." Anderssen, R. S., Braddock, R. D. and Newham, L. T. H. (ed.) 18th World IMACS Congress and MODSIM09 International Congress on Modelling and Simulation. Cairns, Australia 13 - 17 Jul 2009 Canberra, Australia. Modelling and Simulation Society of Australia and New Zealand .

Effect of exit Reynolds number on self-preservation of a plane jet

Mi, Jianchun, Feng, Baoping, Deo, Ravinesh C. and Nathan, Graham J.. 2009. "Effect of exit Reynolds number on self-preservation of a plane jet." Chinese Physics B. 58 (11), pp. 7756-7764.

A continent under stress: interactions, feedbacks and risks associated with impact of modified land cover on Australia's climate

McAlpine, C. A., Syktus, J., Ryan, J. G., Deo, R. C., McKeon, G. M., McGowan, H. A. and Phinn, S. R.. 2009. "A continent under stress: interactions, feedbacks and risks associated with impact of modified land cover on Australia's climate." Global Change Biology. 15 (9), pp. 2206-2223. https://doi.org/10.1111/j.1365-2486.2009.01939.x

Impact of historical land cover change on daily indices of climate extremes including droughts in eastern Australia

Deo, R. C., Syktus, J. I., McAlpine, C. A., Lawrence, P. J., McGowan, H. A. and Phinn, S. R.. 2009. "Impact of historical land cover change on daily indices of climate extremes including droughts in eastern Australia." Geophysical Research Letters. 36 (8), pp. 1-5. https://doi.org/10.1029/2009GL037666

On Australian heat waves: time series analysis of extreme temperature events in Australia, 1950 - 2005

Deo, R. C., McAlpine, C. A., Syktus, J., McGowan, H. A. and Phinn, S.. 2007. "On Australian heat waves: time series analysis of extreme temperature events in Australia, 1950 - 2005." Oxley, Les and Kulasiri, Don (ed.) 17th International Congress on Modelling and Simulation (MODSIM07). Christchurch, New Zealand 10 - 13 Dec 2007 Australia. Modelling and Simulation Society of Australia and New Zealand .

Impact of land cover change on regional climate and El Nino in Australia

Syktus, J., Deo, R. C., McAlpine, C. A., McGowan, H. A. and Phinn, S.. 2007. "Impact of land cover change on regional climate and El Nino in Australia." Oxley, Les and Kulasiri, Don (ed.) 17th International Congress on Modelling and Simulation (MODSIM07). Christchurch, New Zealand 10 - 13 Dec 2007 Australia. Modelling and Simulation Society of Australia and New Zealand .

Experimental investigations of the effect of Reynolds number on a plane jet

Deo, Ravinesh C., Mi, Jianchun and Nathan, Graham J.. 2007. "Experimental investigations of the effect of Reynolds number on a plane jet." Jacobs, Peter A., McIntyre, Tim, Cleary, Matthew J., Buttsworth, David R., Mee, David, Clements, Rose, Morgan, Richard and Lemckert, Charles (ed.) 16th Australasian Fluid Mechanics Conference (AFMC 2007). Gold Coast, Australia 03 - 07 Dec 2007 Brisbane, Australia.

The influence of Reynolds number on a plane jet

Deo, Ravinesh C., Mi, Jianchun and Nathan, Graham J.. 2008. "The influence of Reynolds number on a plane jet." Physics of Fluids. 20 (7). https://doi.org/10.1063/1.2959171

The influence of nozzle-exit geometric profile on statistical properties of a turbulent plane jet

Deo, Ravinesh C., Mi, Jianchun and Nathan, Graham J.. 2007. "The influence of nozzle-exit geometric profile on statistical properties of a turbulent plane jet." Experimental Thermal and Fluid Science. 32 (2), pp. 545-559. https://doi.org/10.1016/j.expthermflusci.2007.06.004

The influence of nozzle aspect ratio on plane jets

Deo, Ravinesh C., Mi, Jianchun and Nathan, Graham J.. 2007. "The influence of nozzle aspect ratio on plane jets." Experimental Thermal and Fluid Science. 31 (8), pp. 825-838. https://doi.org/10.1016/j.expthermflusci.2006.08.009

Total rain accumulation and rain-rate analysis for small tropical Pacific islands: a case study of Suva, Fiji

Kumar, Vickal V., Deo, Ravinesh C. and Ramachandran, Visagaperuman. 2006. "Total rain accumulation and rain-rate analysis for small tropical Pacific islands: a case study of Suva, Fiji." Atmospheric Science Letters. 7 (3), pp. 53-58. https://doi.org/10.1002/asl.131

Fast-convergent iterative scheme for filtering velocity signals and finding Kolmogorov scales

Mi, Jianchun, Deo, Ravinesh C. and Nathan, Graham J.. 2005. "Fast-convergent iterative scheme for filtering velocity signals and finding Kolmogorov scales." Physical Review E. 71 (6), pp. 1-5. https://doi.org/10.1103/PhysRevE.71.066304

Characterization of turbulent jets from high-aspect-ratio rectangular nozzles

Mi, J., Deo, R. C. and Nathan, G. J.. 2005. "Characterization of turbulent jets from high-aspect-ratio rectangular nozzles." Physics of Fluids. 17 (6). https://doi.org/10.1063/1.1928667

An investigation on rainfall patterns and the general circulation in the southwest Pacific region

Deo, Ravinesh C.. 2004. "An investigation on rainfall patterns and the general circulation in the southwest Pacific region." 16th Australia New Zealand Climate Forum: Climate and Water (ANZCF2004). Lorne, Australia 08 - 10 Nov 2004 Lorne, Vic, Australia.

Comparison of turbulent jets issuing from rectangular nozzles with and without sidewalls

Deo, Ravinesh C., Nathan, Graham J. and Mi, Jianchun. 2007. "Comparison of turbulent jets issuing from rectangular nozzles with and without sidewalls." Experimental Thermal and Fluid Science. 32 (2), pp. 596-606. https://doi.org/10.1016/j.expthermflusci.2007.06.009

Dependence of a plane turbulent jet on its nozzle contraction profile

Deo, Ravinesh C., Mi, Jianchun and Nathan, Graham J.. 2005. "Dependence of a plane turbulent jet on its nozzle contraction profile." Jets, Wakes and Separated Flows: International Conference on Jets, Wakes and Separated Flows (ICJWSF) (2005). Mie, Japan 05 - 08 Oct 2005 Mie, Japan.

An investigation of the influence of nozzle aspect ratio on the velocity field of turbulent plane jet

Deo, R. C., Mi, J. and Nathan, G. J.. 2004. "An investigation of the influence of nozzle aspect ratio on the velocity field of turbulent plane jet." Behnia, M., Lin, W. and McBain, G. D. (ed.) 15th Australasian Fluid Mechanics Conference (AFMC 2004). Sydney, Australia 13 - 17 Dec 2004 Sydney, Australia.

The Development of a Novel Quantum Pre-processing Filter to Improve Image Classification Accuracy of Neural Network Models

Riaz, Farina, Abdulla, Shahab, Suzuki, Hajime, Ganguly, Srinjoy, Deo, Ravinesh C. and Hopkins, Susan. 2025. "The Development of a Novel Quantum Pre-processing Filter to Improve Image Classification Accuracy of Neural Network Models ." Journal of Data Science and Intelligent Systems. https://doi.org/10.47852/bonviewJDSIS52024231

Hybrid CNN–GRU model for hourly flood forecasting index: case studies from the Fiji islands

Chand, Ravinesh, Deo, Ravinesh C., Ghimire, Sujan, Nguyen-Huy, Thong and Ali, Mumtaz. 2025. "Hybrid CNN–GRU model for hourly flood forecasting index: case studies from the Fiji islands." Stochastic Environmental Research and Risk Assessment. https://doi.org/10.1007/s00477-025-02964-8

Explainable hybrid deep learning framework for enhancing multi-step solar ultraviolet-B radiation predictions

Prasad, Salvin S., Joseph, Lionel P., Ghimire, Sujan, Deo, Ravinesh C., Downs, Nathan J., Acharya, Rajendra and Yaseen, Zaher M.. 2025. "Explainable hybrid deep learning framework for enhancing multi-step solar ultraviolet-B radiation predictions." Atmospheric Environment. 343. https://doi.org/10.1016/j.atmosenv.2024.120951

Multi‑step solar ultraviolet index prediction: integrating convolutional neural networks with long short‑term memory for a representative case study in Queensland, Australia

AL-Musaylh, Mohan, Al‑Dafaie, Kadhem, Downs, Nathan, Ghimire, Sujan, Ali, Mumtaz, Yaseen, Zaher Mundher, Igoe, Damien P., Deo, Ravinesh C., Paris, Alfo V. and A. Jebar, Mustapha A.. 2025. "Multi‑step solar ultraviolet index prediction: integrating convolutional neural networks with long short‑term memory for a representative case study in Queensland, Australia." Modeling Earth Systems and Environment. 11. https://doi.org/https://link.springer.com/article/10.1007/s40808-024-02282-y

Explainable deeply-fused nets electricity demand prediction model: Factoring climate predictors for accuracy and deeper insights with probabilistic confidence interval and point-based forecasts

Ghimire, Sujan, AL-Musaylh, Mohanad S., Nguyen-Huy, Thong, Deo, Ravinesh C., Acharya, Rajendra, Casillas-Perez, David, Yaseen, Zaher Mundher and Salcedo-sanz, Sancho. 2025. "Explainable deeply-fused nets electricity demand prediction model: Factoring climate predictors for accuracy and deeper insights with probabilistic confidence interval and point-based forecasts." Applied Energy. 378 (Part A). https://doi.org/10.1016/j.apenergy.2024.124763

The mitigating effect of street trees, urban flora, and the suburban environment on seasonal peak UV indices: A case study from Brisbane, Australia

Downs, Nathan James, Amar, Abdurazaq, Dearnaley, John, Butler, Harry, Dekeyser, Stijn, Igoe, Damien, Parisi, Alfio V., Raj, Nawin, Deo, Ravinesh and Turner, Joanna. 2025. "The mitigating effect of street trees, urban flora, and the suburban environment on seasonal peak UV indices: A case study from Brisbane, Australia." Photochemistry and Photobiology. 101 (1), pp. 251-266. https://doi.org/10.1111/php.13988

The Application of Quantum Pre-processing Filter for Binary Image Classification with Small Samples

Riaz, Farina, Abdulla, Shahab, Suzuki, Hajime, Ganguly, Srinjoy, Deo, Ravinesh C. and Hopkins, Susan. 2024. "The Application of Quantum Pre-processing Filter for Binary Image Classification with Small Samples ." Journal of Data Science and Intelligent Systems. 3 (2), pp. 109-116. https://doi.org/10.47852/bonviewJDSIS42024229

A Comprehensive Review of UAV-UGV Collaboration: Advancements and Challenges

Munasinghe, Isuru, Perera, Asanka and Deo, Ravinesh C.. 2024. "A Comprehensive Review of UAV-UGV Collaboration: Advancements and Challenges." Journal of Sensor and Actuator Networks. 13 (6). https://doi.org/10.3390/jsan13060081

Retinal Health Screening Using Artificial Intelligence with Digital Fundus Images: A Review of the Last Decade (2012-2023)

Islam, Saad, Deo, Ravinesh C., Barua, Prabal Datta, Soar, Jeffrey, Yu, Ping and Acharya, U. Rajendra. 2024. "Retinal Health Screening Using Artificial Intelligence with Digital Fundus Images: A Review of the Last Decade (2012-2023)." IEEE Access. 12, pp. 176630-176685. https://doi.org/10.1109/ACCESS.2024.3477420

Forecasting River Water Temperature Using Explainable Artificial Intelligence and Hybrid Machine Learning: Case Studies in Menindee Region in Australia

Briceno Medina, Leyde, Joehnk, Klaus, Deo, Ravinesh C., Ali, Mumtaz, Prasad, Salvin S. and Downs, Nathan. 2024. "Forecasting River Water Temperature Using Explainable Artificial Intelligence and Hybrid Machine Learning: Case Studies in Menindee Region in Australia." Water. 16 (24). https://doi.org/10.3390/w16243720

Explainable artificial intelligence-machine learning models to estimate overall scores in tertiary preparatory general science course

Ghimire, Sujan, Abdulla, Shahab, Joseph, Lionel P., Prasad, Salvin, Murphy, Angela, Devi, Aruna, Barua, Prabal Datta, Deo, Ravinesh C., Acharya, Rajendra and Yaseen, Zaher Mundher. 2024. "Explainable artificial intelligence-machine learning models to estimate overall scores in tertiary preparatory general science course." Computers and Education: Artificial Intelligence. 7. https://doi.org/10.1016/j.caeai.2024.100331

Forecasting Multi-Step Soil Moisture with Three-Phase Hybrid Wavelet-Least Absolute Shrinkage Selection Operator-Long Short-Term Memory Network (moDWT-Lasso-LSTM) Model

Jayasinghe, W. J. M. Lakmini Prarthana, Deo, Ravinesh C., Raj, Nawin, Ghimire, Sujan, Yaseen, Zaher Mundher, Nguyen-Huy, Thong and Ghahramani, Afshin. 2024. "Forecasting Multi-Step Soil Moisture with Three-Phase Hybrid Wavelet-Least Absolute Shrinkage Selection Operator-Long Short-Term Memory Network (moDWT-Lasso-LSTM) Model." Water. 16 (21), p. 3133. https://doi.org/10.3390/w16213133

Artificial Intelligence-Empowered Doppler Weather Profile for Low-Earth-Orbit Satellites

Sharma, Ekta, Deo, Ravinesh C., Davey, Christopher P and Carter, Brad D.. 2024. "Artificial Intelligence-Empowered Doppler Weather Profile for Low-Earth-Orbit Satellites." Sensors. 24 (16). https://doi.org/10.3390/s24165271

Wavelet-fusion image super-resolution model with deep learning for downscaling remotely-sensed, multi-band spectral albedo imagery

Karalasingham, Sagthitharan, Deo, Ravinesh C., Casillas-Perez, David, Raj, Nawin and Salcedo-sanz, Sancho. 2024. "Wavelet-fusion image super-resolution model with deep learning for downscaling remotely-sensed, multi-band spectral albedo imagery." Remote Sensing Applications: Society and Environment. 36. https://doi.org/10.1016/j.rsase.2024.101333

Half-hourly electricity price prediction with a hybrid convolution neural network-random vector functional link deep learning approach

Ghimire, Sujan, Deo, Ravinesh C., Casillas-Perez, David, Sharma, Ekta, Salcedo-sanz, Sancho, Barua, Prabal and Acharya, U. Rajendra. 2024. "Half-hourly electricity price prediction with a hybrid convolution neural network-random vector functional link deep learning approach." Applied Energy. 374. https://doi.org/10.1016/j.apenergy.2024.123920

Towards next-generation federated learning: A case study on privacy attacks in artificial intelligence systems

Sharma, Ekta, Deo, Ravinesh C, Davey, Christopher P., Carter, Brad D. and Salcedo-sanz, Sancho. 2024. "Towards next-generation federated learning: A case study on privacy attacks in artificial intelligence systems." 2024 IEEE Conference on Artificial Intelligence (CAI 2024). Singapore 25 - 27 Jun 2024 United States. IEEE (Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/CAI59869.2024.00259

Poster: Cloud Computing with AI-empowered Trends in Software-Defined Radios: Challenges and Opportunities

Sharma, Ekta, Deo, Ravinesh C., Davey, Christopher P., Carter, Brad D. and Salcedo-sanz, Sancho. 2024. "Poster: Cloud Computing with AI-empowered Trends in Software-Defined Radios: Challenges and Opportunities." 2024 IEEE 25th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM 2024). Perth, Australia 04 - 07 Jun 2024 United States. IEEE (Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/WoWMoM60985.2024.00054

Atmospheric Visibility and Cloud Ceiling Predictions With Hybrid IIS-LSTM Integrated Model: Case Studies for Fiji's Aviation Industry

Raj, Shiveel, Deo, Ravinesh C., Sharma, Ekta, Prasad, Ramendra, Dinh, Toan and Salcedo-sanz, Sancho. 2024. "Atmospheric Visibility and Cloud Ceiling Predictions With Hybrid IIS-LSTM Integrated Model: Case Studies for Fiji's Aviation Industry." IEEE Access. 12, pp. 72530-72543. https://doi.org/10.1109/ACCESS.2024.3401091

Point-based and probabilistic electricity demand prediction with a Neural Facebook Prophet and Kernel Density Estimation model

Ghimire, Sujan, Deo, Ravinesh C., Pourmousavi, S. Ali, Casillas-Perez, David and Salcedo-sanz, Sancho. 2024. "Point-based and probabilistic electricity demand prediction with a Neural Facebook Prophet and Kernel Density Estimation model." Engineering Applications of Artificial Intelligence. 135. https://doi.org/10.1016/j.engappai.2024.108702

End-to-end learning of adaptive coded modulation schemes for resilient wireless communications

Davey, Christopher P., Shakeel, Ismail, Deo, Ravinesh C., Sharma, Ekta, Salcedo-sanz, Sancho and Soar, Jeffrey. 2024. "End-to-end learning of adaptive coded modulation schemes for resilient wireless communications." Applied Soft Computing. 159. https://doi.org/10.1016/j.asoc.2024.111672

Deep Learning Based Over-the-Air Training of Wireless Communication Systems without Feedback

Davey, Christopher P., Shakeel, Ismail, Deo, Ravinesh C. and Salcedo-sanz, Sancho. 2024. "Deep Learning Based Over-the-Air Training of Wireless Communication Systems without Feedback." Sensors. 24 (10). https://doi.org/10.3390/s24102993

A playground shade index for standardising ultraviolet protection assessments of open, mixed and protected outdoor recreational spaces

Downs, Nathan, Butler, Harry, Dexter, Benjamin, Raj, Nawin, Downs, Melanie, Turner, Joanna, Dekeyser, Stijn, Deo, Ravinesh, Vanos, Jennifer, Igoe, Damien and Parisi, Alfio V. 2024. "A playground shade index for standardising ultraviolet protection assessments of open, mixed and protected outdoor recreational spaces." 6th International conference UV and Skin Cancer Prevention. Brisbane, Australia 11 - 15 Sep 2024 Australia.

Multi-Step-Ahead Wind Speed Forecast System: Hybrid Multivariate Decomposition and Feature Selection-Based Gated Additive Tree Ensemble Model

Joseph, Lionel P., Deo, Ravinesh C., Casillas-Perez, David, Prasad, Ramendra, Raj, Nawin and Salcedo-sanz, Sancho. 2024. "Multi-Step-Ahead Wind Speed Forecast System: Hybrid Multivariate Decomposition and Feature Selection-Based Gated Additive Tree Ensemble Model." IEEE Access. 12, pp. 58750-58777. https://doi.org/10.1109/ACCESS.2024.3392899

Deep Learning-Assisted Sensitive 3C-SiC Sensor for Long-Term Monitoring of Physical Respiration

Tran, Thi Lap, Nguyen, Duy Van, Nguyen, Hung, Nguyen, Thi Phuoc Van, Song, Pingan, Deo, Ravinesh C, Moloney, Clint, Dao, Viet Dung, Nguyen, Nam-Trung and Dinh, Toan. 2024. "Deep Learning-Assisted Sensitive 3C-SiC Sensor for Long-Term Monitoring of Physical Respiration." Advanced Sensor Research. 3 (8). https://doi.org/10.1002/adsr.202300159

Copula-Probabilistic Flood Risk Analysis with an Hourly Flood Monitoring Index

Chand, Ravinesh, Nguyen-Huy, Thong, Deo, Ravinesh C., Ghimire, Sujan, Ali, Mumtaz and Ghahramani, Afshin. 2024. "Copula-Probabilistic Flood Risk Analysis with an Hourly Flood Monitoring Index." Water. 16 (11). https://doi.org/10.3390/w16111560

Short-term wind speed forecasting using an optimized three-phase convolutional neural network fused with bidirectional long short-term memory network model

Joseph, Lionel P., Deo, Ravinesh C., Casillas-Perez, David, Prasad, Ramendra, Raj, Nawin and Salcedo-sanz, Sancho. 2024. "Short-term wind speed forecasting using an optimized three-phase convolutional neural network fused with bidirectional long short-term memory network model." Applied Energy. 359. https://doi.org/10.1016/j.apenergy.2024.122624

Probabilistic-based electricity demand forecasting with hybrid convolutional neural network-extreme learning machine model

Ghimire, Sujan, Deo, Ravinesh C., Casillas-Perez, David, Salcedo-sanz, Sancho, Pourmousavi, S. Ali and Acharya, U. Rajendra. 2024. "Probabilistic-based electricity demand forecasting with hybrid convolutional neural network-extreme learning machine model." Engineering Applications of Artificial Intelligence. 132. https://doi.org/10.1016/j.engappai.2024.107918

Electricity demand error corrections with attention bi-directional neural networks

Ghimire, Sujan, Deo, Ravinesh C., Casillas-Perez, David and Salcedo-sanz, Sancho. 2024. "Electricity demand error corrections with attention bi-directional neural networks." Energy. 291. https://doi.org/10.1016/j.energy.2023.129938

Micromachined Mechanical Resonant Sensors: From Materials, Structural Designs to Applications

Dinh, Toan, Rais-Zadeh, Mina, Nguyen, Thanh, Phan, Hoang-Phuong, Song, Pingan, Deo, Ravinesh, Dao, Dzung, Nguyen, Nam-Trung and Bell, John. 2024. "Micromachined Mechanical Resonant Sensors: From Materials, Structural Designs to Applications." Advanced Materials Technologies. 9 (2). https://doi.org/10.1002/admt.202300913

Machine learning for expediting next-generation of fire-retardant polymer composites

Jafari, Pooya, Zhang, Ruoran, Huo, Siqi, Wang, Qingsheng, Yong, Jianming, Hong, Min, Deo, Ravinesh, Wang, Hao and Song, Pingan. 2024. "Machine learning for expediting next-generation of fire-retardant polymer composites." Composites Communications. 45. https://doi.org/10.1016/j.coco.2023.101806

Very short-term solar ultraviolet-A radiation forecasting system with cloud cover images and a Bayesian optimized interpretable artificial intelligence model

Prasad, Salvin Sanjesh, Deo, Ravinesh Chand, Downs, Nathan James, Casillas-Perez, David, Salcedo-sanz, Sancho and Parisi, Alfio Venerando. 2024. "Very short-term solar ultraviolet-A radiation forecasting system with cloud cover images and a Bayesian optimized interpretable artificial intelligence model ." Expert Systems with Applications. 236. https://doi.org/10.1016/j.eswa.2023.121273

Short-term wave power forecasting with hybrid multivariate variational mode decomposition model integrated with cascaded feedforward neural networks

Ali, Mumtaz, Prasad, Ramendra, Jamei, Mehdi, Malik, Anurag, Xiang, Yong, Abdulla, Shahab, Deo, Ravinesh C., Farooque, Aitazaz A. and Labban, Abdulhaleem H.. 2024. "Short-term wave power forecasting with hybrid multivariate variational mode decomposition model integrated with cascaded feedforward neural networks." Renewable Energy. 221. https://doi.org/10.1016/j.renene.2023.119773

Two-step deep learning framework with error compensation technique for short-term, half-hourly electricity price forecasting

Ghimire, Sujan, Deo, Ravinesh C., Casillas-Perez, David and Salcedo-sanz, Sancho. 2024. "Two-step deep learning framework with error compensation technique for short-term, half-hourly electricity price forecasting." Applied Energy. 353 (Part A). https://doi.org/10.1016/j.apenergy.2023.122059

Hybrid Deep Learning Model for Wave Height Prediction in Australia's Wave Energy Region

Ahmed, Abul Abrar Masrur, Jui, S Janifer Jabin, AL-Musaylh, Mohanad S., Raj, Nawin, Saha, Reepa, Deo, Ravinesh C and Saha, Sanjoy Kumar. 2024. "Hybrid Deep Learning Model for Wave Height Prediction in Australia's Wave Energy Region." Applied Soft Computing. 150. https://doi.org/10.1016/j.asoc.2023.111003

Author Correction: Explainable AI approach with original vegetation data classifies spatio‑temporal nitrogen in flows from ungauged catchments to the Great Barrier Reef

O’Sullivan, Cherie M., Deo, Ravinesh C. and Ghahramani, Afshin. 2023. "Author Correction: Explainable AI approach with original vegetation data classifies spatio‑temporal nitrogen in flows from ungauged catchments to the Great Barrier Reef." Scientific Reports. 13 (1). https://doi.org/10.1038/s41598-023-48938-0

Channel-Agnostic Training of Transmitter and Receiver for Wireless Communications

Davey, Christopher P., Shakeel, Ismail, Deo, Ravinesh C. and Salcedo-sanz, Sancho. 2023. "Channel-Agnostic Training of Transmitter and Receiver for Wireless Communications ." Sensors. 23 (24). https://doi.org/10.3390/s23249848

Deep Image Analysis for Microalgae Identification

Soar, Jeffrey, Lih, Oh Shu, Wen, Loh Hui, Ward, Aleth, Sharma, Ekta, Deo, Ravinesh C., Barua, Prabal Datta, Tan, Ru-San, Rinen, Eliezer and Acharya, Rajendra. 2023. "Deep Image Analysis for Microalgae Identification." Lecture notes in computer science. Switzerland . Springer. pp. 280-292

Statistical and spatial analysis for soil heavy metals over the Murray-Darling river basin in Australia

Tao, Hai, Al-Hilali, Aqeel Ali, Ahmed, Ali M., Mussa, Zainab Haider, Falah, Mayadah W., Abed, Salwan Ali, Deo, Ravinesh, Jawad, Ali H., Maulud, Khairul Nizam Abdul, Latif, Mohd Talib and Yaseen, Zaher Mundher. 2023. "Statistical and spatial analysis for soil heavy metals over the Murray-Darling river basin in Australia." Chemosphere. 317. https://doi.org/10.1016/j.chemosphere.2023.137914

Enhanced joint hybrid deep neural network explainable artificial intelligence model for 1-hr ahead solar ultraviolet index prediction

Prasad, Salvin S., Deo, Ravinesh C., Salcedo-sanz, Sancho, Downs, Nathan J., Casillas-Perez, David and Parisi, Alfio V.. 2023. "Enhanced joint hybrid deep neural network explainable artificial intelligence model for 1-hr ahead solar ultraviolet index prediction." Computer Methods and Programs in Biomedicine. 241. https://doi.org/10.1016/j.cmpb.2023.107737

Ampelomyces mycoparasites of powdery mildews–a review

Prahl, Rosa E., Khan, Shahjahan and Deo, Ravinesh C.. 2023. "Ampelomyces mycoparasites of powdery mildews–a review." Canadian Journal of Plant Pathology. 45 (4), pp. 391-404. https://doi.org/10.1080/07060661.2023.2206378

A fuzzy-based cascade ensemble model for improving extreme wind speeds prediction

Pelaez-Rodriguez, C., Perez-Aracil, J., Prieto-Godino, L., Ghimire, S., Deo, R. and Salcedo-sanz, S.. 2023. "A fuzzy-based cascade ensemble model for improving extreme wind speeds prediction." Journal of Wind Engineering and Industrial Aerodynamics. 240. https://doi.org/10.1016/j.jweia.2023.105507

Explainable AI approach with original vegetation data classifies spatio-temporal nitrogen in flows from ungauged catchments to the Great Barrier Reef

O’Sullivan, Cherie M., Deo, Ravinesh C. and Ghahramani, Afshin. 2023. "Explainable AI approach with original vegetation data classifies spatio-temporal nitrogen in flows from ungauged catchments to the Great Barrier Reef." Scientific Reports. 13 (1). https://doi.org/10.1038/s41598-023-45259-0

A Novel Attention-Based Model for Semantic Segmentation of Prostate Glands Using Histopathological Images

Inamdar, Mahesh Anil, Raghavendra, U., Gudigar, Anjan, Bhandary, Sarvesh, Salvi, Massimo, Deo, Ravinesh C., Barua, Prabal Datta, Ciaccio, Edward J., Molinari, Filippo and Acharya, RU. Rajendra. 2023. "A Novel Attention-Based Model for Semantic Segmentation of Prostate Glands Using Histopathological Images." IEEE Access. 11, pp. 108982-108994. https://doi.org/10.1109/ACCESS.2023.3321273

Efficient daily electricity demand prediction with hybrid deep-learning multi-algorithm approach

Ghimire, Sujan, Deo, Ravinesh C., Casillas-Perez, David and Salcedo-sanz, Sancho. 2023. "Efficient daily electricity demand prediction with hybrid deep-learning multi-algorithm approach." Energy Conversion and Management. 297. https://doi.org/10.1016/j.enconman.2023.117707

Automated detection of airflow obstructive diseases: A systematic review of the last decade (2013-2022)

Xu, Shuting, Deo, Ravinesh C, Soar, Jeffrey, Barua, Prabal Datta, Faust, Oliver, Homaira, Nusrat, Jaffe, Adam, Kabir, Arm Luthful and Acharya, U. Rajendra. 2023. "Automated detection of airflow obstructive diseases: A systematic review of the last decade (2013-2022)." Computer Methods and Programs in Biomedicine. 241. https://doi.org/10.1016/j.cmpb.2023.107746

Brain tumor detection and screening using artificial intelligence techniques: Current trends and future perspectives

Raghavendra, U., Gudigar, Anjan, Paul, Aritra, Goutham, T.S., Inamdar, Mahesh Anil, Hegde, Ajay, Dev, Aruna, Ooi, Chui Ping, Deo, Ravinesh C., Barua, Prabal Datta, Molinari, Filippo, Ciaccio, Edward J. and Acharya, U. Rajendra. 2023. "Brain tumor detection and screening using artificial intelligence techniques: Current trends and future perspectives." Computers in Biology and Medicine. 163. https://doi.org/10.1016/j.compbiomed.2023.107063

Application of Entropy for Automated Detection of Neurological Disorders With Electroencephalogram Signals: A Review of the Last Decade (2012-2022)

Jui, S. Janifer Jabin, Deo, Ravinesh C. Deo, Barua, Prabal Datta, Devi, Aruna, Soar, Jeffrey and Acharya, U. Rajendra. 2023. "Application of Entropy for Automated Detection of Neurological Disorders With Electroencephalogram Signals: A Review of the Last Decade (2012-2022)." IEEE Access. 11, pp. 71905-71924. https://doi.org/10.1109/ACCESS.2023.3294473

Integrated Multi-Head Self-Attention Transformer model for electricity demand prediction incorporating local climate variables

Ghimire, Sujan, Nguyen-Huy, Thong, AL-Musaylh, Mohanad S., Deo, Ravinesh C., Casillas-Perez, David and Salcedo-sanz, Sancho. 2023. "Integrated Multi-Head Self-Attention Transformer model for electricity demand prediction incorporating local climate variables." Energy and AI. 14. https://doi.org/10.1016/j.egyai.2023.100302