MARS model for prediction of short- and long-term global solar radiation
Edited book (chapter)
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
| Chapter Title | MARS model for prediction of short- and long-term global solar radiation |
|---|---|
| Book Chapter Category | Edited book (chapter) |
| ERA Publisher ID | 1821 |
| Book Title | Predictive modelling for energy management and power systems engineering |
| Authors | Balalla, Dilki T. (Author), Nguyen-Huy, Thong (Author) and Deo, Ravinesh (Author) |
| Editors | Deo, Ravinesh, Samui, Pijush and Roy, Sanjiban Sekhar |
| Page Range | 391-436 |
| Chapter Number | 13 |
| Number of Pages | 46 |
| Year | 2021 |
| Publisher | Elsevier |
| Place of Publication | Amsterdam, Netherlands |
| ISBN | 9780128177723 |
| Web Address (URL) | https://www.elsevier.com/books/predictive-modelling-for-energy-management-and-power-systems-engineering/deo/978-0-12-817772-3 |
| Abstract | The intention of this research was to try and address the research question 'Is machine learning algorithm, Multivariate Adaptive Regression Splines model, a versatile forecasting model for solar radiation?' The objective of this chapter is to develop a machine learning (ML) algorithm to validate and assess errors for the method used to forecast solar radiation based on historical data. The specific aims are to construct (1) short-term (daily) global solar radiation model using the MARS algorithm considering the nonlinear behavior of surface-level solar radiation with its predictor variables; and (2) long-term (monthly) global solar radiation model using the MARS algorithm to enable the solar energy assessment over a long-term period and considering. This chapter carried out short-term and long-term solar radiation forecasting model development for regional Queensland. Short-term forecasting provides predictions up to 7 days ahead. These forecasts are valuable for grid operators in order to make important decisions for grid operation. It will provide valuable information regarding the time scheduling of power systems (Wan et al., 2015). Long-term forecasting has been carried out considering 1-month ahead, 3-month, and 6-month ahead forecast. This is useful for energy companies to make decisions and negotiate contracts with energy producers (Martı´n et al., 2010) and also for effective operation and maintenance planning of solar power systems (Koca et al., 2011). The information gathered from the seasonal analysis can be used for studying the seasonal patterns of the solar energy and for Seasonal Thermal Energy Storage (i.e., STES) (Allen et al., 1984) where the heat acquired from solar collectors in hot months can be stored for future use when needed, including during winter months. |
| Keywords | solar energy; forecasting |
| ANZSRC Field of Research 2020 | 419999. Other environmental sciences not elsewhere classified |
| 469999. Other information and computing sciences not elsewhere classified | |
| Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
| Byline Affiliations | School of Sciences |
| Centre for Applied Climate Sciences | |
| Institution of Origin | University of Southern Queensland |
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Taherizadeh, Mehrnoosh, Niknam, Arman, Nguyen-Huy, Thong, Mezősi, Gábor and Sarli, Reza. 2023. "Flash flood-risk areas zoning using integration of decision-making trial and evaluation laboratory, GIS-based analytic network process and satellite-derived information." Natural Hazards. 118 (3), p. 2309–2335. https://doi.org/10.1007/s11069-023-06089-5Revealing the effect of an industrial flash flood on vegetation area: a case study of Khusheh Mehr in Maragheh-Bonab Plain, Iran
Taherizadeh, Mehrnoosh, Khushemehr, Javid Hojabri, Niknam, Arman, Nguyen-Huy, Thong and Mezősi, Gábor. 2023. "Revealing the effect of an industrial flash flood on vegetation area: a case study of Khusheh Mehr in Maragheh-Bonab Plain, Iran." Remote Sensing Applications: Society and Environment. 32. https://doi.org/10.1016/j.rsase.2023.101016The 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.2022.114493Comparison 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.2023.105634A 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.2023.127430Climatology and composite evolution of flash drought over Australia and its vegetation impacts
Nguyen, Hanh, Wheeler, Mattew C., Otkin, Jason A., Nguyen-Huy, Thong and Cowan, Timothy. 2023. "Climatology and composite evolution of flash drought over Australia and its vegetation impacts." Journal of Hydrometeorology. 24 (6), p. 1087–1101. https://doi.org/10.1175/JHM-D-22-0033.1Digital Farming: An Overview of Its Fundamental Components and Applications
Nguyen-Huy, Thong. 2023. "Digital Farming: An Overview of Its Fundamental Components and Applications." The 4th International Conference of Food Security and Sustainable Agriculture in the Tropics. South Sulawesi, Indonesia 15 - 16 Feb 2023 Indonesia.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/s23052753Near 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.2022.12.123Downscaling 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.2023.3236253Developing 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.2022.107305Cloud 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.2022.12.048Deep 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.2021.3135362Designing 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.2021.3065939Pattern 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.2022.160240The 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.13745Using 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.2022.3221762Modelling 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-yVapour pressure deficit determines critical thresholds for global coffee production under climate change
Kath, Jarrod, Craparo, Alessandro, Fong, Youyi, Byrareddy, Vivekananda, Davis, Aaron P., King, Rachel, Nguyen-Huy, Thong, van Asten, Piet J. A., Marcussen, Torben, Mushtaq, Shahbaz, Stone, Roger and Power, Scott. 2022. "Vapour pressure deficit determines critical thresholds for global coffee production under climate change." Nature Food. 3, pp. 871-880. https://doi.org/10.1038/s43016-022-00614-8Student 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.2022.3168322Rapid 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/10.1080/10106049.2022.2048902Multi-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.2022.109048Suspended 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.2022.127963Delineating 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/agronomy12061268Coupled 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/s41598-022-09482-5Forecasting 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/s00477-022-02188-0Improved 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.2022.03.120Efficient 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.e00429Hybrid 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.2022.104860Boosting 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.2022.119063Machine 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.2022.106157Quantum 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.2.2.34754.66245A satellite-based Standardized Antecedent Precipitation Index (SAPI) for mapping extreme rainfall risk in Myanmar
Nguyen-Huy, Thong, Kath, Jarrod, Nagler, Thomas, Khaung, Ye, Aung, Thee Su Su, Mushtaq, Shahbaz, Marcussen, Torben and Stone, Roger. 2022. "A satellite-based Standardized Antecedent Precipitation Index (SAPI) for mapping extreme rainfall risk in Myanmar." Remote Sensing Applications: Society and Environment. 26, pp. 1-19. https://doi.org/10.1016/j.rsase.2022.100733Deep 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.2022.111759Basin 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.2022.158359Introductory 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/su141711070Kernel 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/rs14051136Cloud 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.2022.3153475Development 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.2022.127534Integrative 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.2022.114711An 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.2021.808339Stacked 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/en15031061Texture 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.2022.110731General equilibrium impact evaluation of food top-up induced by households’ renewable power self-supply in 141 regions
Nguyen, Duong Binh, Nong, Duy, Simshauser, Paul and Nguyen-Huy, Thong. 2022. "General equilibrium impact evaluation of food top-up induced by households’ renewable power self-supply in 141 regions." Applied Energy. 306 (Part B), pp. 1-13. https://doi.org/10.1016/j.apenergy.2021.118126Classification 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.2021.151139Copula-based statistical modelling of synoptic-scale climate indices for quantifying and managing agricultural risks in Australia
Nguyen-Huy, Thong. 2020. "Copula-based statistical modelling of synoptic-scale climate indices for quantifying and managing agricultural risks in Australia." Bulletin of the Australian Mathematical Society. 101 (1), pp. 166-169. https://doi.org/10.1017/S0004972719001217Drought Outlook Products Review
Cobon, David, Nguyen-Huy, Thong and Reardon-Smith, Kate. 2019. Drought Outlook Products Review. Toowoomba, Australia. University of Southern Queensland.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/s41893-019-0397-9Bat 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/s12665-018-7662-5Characteristics 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-zThe 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/s1266Uncertainty 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-zMethodology for producing the Drought Monitor
Pudmenzky, Christa, Guillory, Laura, Cobon, David H. and Nguyen-Huy, Thong. 2020. Methodology for producing the Drought Monitor. Toowoomba, Queensland. University of Southern Queensland.Northern Australia Climate Program: supporting adaptation in rangeland grazing systems through more targeted climate forecasts, improved drought information and an innovative extension program
Cobon, David, Jarvis, Chelsea, Reardon-Smith, Kate, Guillory, Laura, Pudmenzky, Christa, Nguyen-Huy, Thong, Mushtaq, Shahbaz and Stone, Roger. 2021. "Northern Australia Climate Program: supporting adaptation in rangeland grazing systems through more targeted climate forecasts, improved drought information and an innovative extension program." The Rangeland Journal. 43 (3), pp. 87-100. https://doi.org/10.1071/RJ20074Novel 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.2022.119111New 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.2022.154722Global disparities in agricultural climate index-based insurance research
Adeyinka, Adewuyi Ayodele, Kath, Jarrod, Nguyen-Huy, Thong, Mushtaq, Shahbaz, Souvignet, Maxime, Range, Matthias and Barratt, Jonathan. 2022. "Global disparities in agricultural climate index-based insurance research." Climate Risk Management. 35, pp. 1-15. https://doi.org/10.1016/j.crm.2022.100394Drought outlook validation using ACCESS-S2 hindcast
Nguyen-Huy, Thong and Cobon, David. 2022. Drought outlook validation using ACCESS-S2 hindcast. Northern Australia Climate Program (NACP).Systemic risk management in farming - geographic distribution and diversity
Nguyen-Huy, Thong. 2022. "Systemic risk management in farming - geographic distribution and diversity." Future Drought Fund’s 2022 Science to Practice Forum. 07 - 08 Jun 2022 Australia.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