460207. Modelling and simulation
| Title | 460207. Modelling and simulation |
|---|---|
| Parent | 4602. Artificial intelligence |
Latest research outputs
Sort by Date Title
AI enabled RPM for Mental Health Facility
Shaik, Thanveer, Tao, Xiaohui, Higgins, Niall, Xie, Haoran, Gururajan, Raj and Zhou, Xujuan. 2022. "AI enabled RPM for Mental Health Facility." 1st ACM Workshop on Mobile and Wireless Sensing for Smart Healthcare (WMSSH 2022). Sydney, Australia 21 Oct 2022 New York, United States. https://doi.org/10.1145/3556551.3561191Paper
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.2022.109048Article
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/s41598-022-09482-5Article
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/s00477-022-02188-0Article
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.2022.03.120Article
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.e00429Article
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.2022.104860Article
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.2022.119063Article
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.2022.106157Article
An EEG based real-time epilepsy seizure detection approach using discrete wavelet transform and machine learning methods
Shen, Mingkan, Wen, Peng, Song, Bo and Li, Yan. 2022. "An EEG based real-time epilepsy seizure detection approach using discrete wavelet transform and machine learning methods." Biomedical Signal Processing and Control. 77, pp. 1-8. https://doi.org/10.1016/j.bspc.2022.103820Article
Real-Time Depth of Anaesthesia Assessment Based on Hybrid Statistical Features of EEG
Huang, Yi, Wen, Peng, Song, Bo and Li, Yan. 2022. "Real-Time Depth of Anaesthesia Assessment Based on Hybrid Statistical Features of EEG." Sensors. 22 (16). https://doi.org/10.3390/s22166099Article
Mobile phone enabled mental health monitoring to enhance diagnosis for severity assessment of behaviours: a review
Gopalakrishnan, Abinaya, Venkataraman, Revathi, Gururajan, Raj, Xujuan, Zhou and Genrich, Rohan. 2022. "Mobile phone enabled mental health monitoring to enhance diagnosis for severity assessment of behaviours: a review." PeerJ Computer Science. 8, pp. 1-34. https://doi.org/10.7717/peerj-cs.1042Article
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.2022.111759Article
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/su141711070Article
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/rs14051136Article
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.2022.3153475Article
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.2022.127534Article
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.2022.114711Article
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/en15031061Article
Novel large scale brain network models for EEG epileptic pattern generations
Al-Hossenat, Auhood, Song, Bo, Wen, Peng and Li, Yan. 2022. "Novel large scale brain network models for EEG epileptic pattern generations." Expert Systems with Applications. 194. https://doi.org/10.1016/j.eswa.2021.116477Article
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/s12665-018-7662-5Article
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/s1266Article
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-zArticle
Feature-aware unsupervised learning with joint variational attention and automatic clustering
Wang, Ru, Li, Lin, Wang, Peipei, Tao, Xiaohui and Liu, Peiyu. 2021. "Feature-aware unsupervised learning with joint variational attention and automatic clustering." 25th International Conference on Pattern Recognition (ICPR 2020). Milan, Italy 10 - 15 Jan 2021 United States. https://doi.org/10.1109/ICPR48806.2021.9412522Paper
Learning Cooperative Max-Pressure Control by Leveraging Downstream Intersections Information for Traffic Signal Control
Peng, Yuquan, Li, Lin, Xie, Qing and Tao, Xiaohui. 2021. "Learning Cooperative Max-Pressure Control by Leveraging Downstream Intersections Information for Traffic Signal Control." U, Leong Hou, Spaniol, Marc, Sakurai, Yasushi and Chen, Junying (ed.) 5th International Joint Conference on Asia-Pacific Web and Web-Age Information Management, Part II (APWeb-WAIM 2021). Guangzhou, China 23 - 25 Aug 2021 Switzerland. Springer. https://doi.org/10.1007/978-3-030-85899-5_29Paper
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.2022.119111Article
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.2022.154722Article
A Two-Stream Graph Convolutional Neural Network for Dynamic Traffic Flow Forecasting
Li, Zhaoyang, Li, Lin, Peng, Yuquan and Tao, Xiaohui. 2020. "A Two-Stream Graph Convolutional Neural Network for Dynamic Traffic Flow Forecasting." Alamaniotis, Miltos and Pan, Shimei (ed.) 32nd IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2020). Baltimore, United States 09 - 11 Nov 2020 Piscataway, United States. https://doi.org/10.1109/ICTAI50040.2020.00063Paper
A federated learning based semi-supervised credit prediction approach enhanced by multi-layer label mean
Li, Lin, Long, Sijie, Bi, Jiaxiu, Wang, Guowei, Zhang, Jiawei and Tao, Xiaohui. 2021. "A federated learning based semi-supervised credit prediction approach enhanced by multi-layer label mean." Web Intelligence. 19 (4), pp. 329-342. https://doi.org/10.3233/WEB-210476Article
Contribution of climate models and APSIM phenological parameters to uncertainties in spring wheat simulations: application of SUFI-2 algorithm in northeast Australia
Collins, Brian, Najeeb, Ullah, Luo, Qunying and Tan, Daniel K. Y.. 2022. "Contribution of climate models and APSIM phenological parameters to uncertainties in spring wheat simulations: application of SUFI-2 algorithm in northeast Australia." Journal of Agronomy and Crop Science. 208 (2), pp. 225-242. https://doi.org/10.1111/jac.12575Article
Two-Stream Graph Convolutional Neural Network for Dynamic Traffic Flow Forecasting
Li, Zhaoyang, Li, Lin and Tao, Xiaohui. 2022. "Two-Stream Graph Convolutional Neural Network for Dynamic Traffic Flow Forecasting." Journal of Frontiers of Computer Science and Technology. 16 (2), pp. 384-394. https://doi.org/10.3778/j.issn.1673-9418.2009097Article
Designing a Multi-Stage Expert System for daily ocean wave energy forecasting: A multivariate data decomposition-based approach
Jamei, Mehdi, Ali, Mumtaz, Karbasi, Masoud, Xiang, Yong, Ahmadianfar, Iman and Yaseen, Zaher Mundher. 2022. "Designing a Multi-Stage Expert System for daily ocean wave energy forecasting: A multivariate data decomposition-based approach ." Applied Energy. 326, pp. 1-24. https://doi.org/10.1016/j.apenergy.2022.119925Article
Artificial Intelligence and Clean Air: Development of Novel Algorithms with Machine Learning and Deep Learning
Sharma, Ekta. 2022. Artificial Intelligence and Clean Air: Development of Novel Algorithms with Machine Learning and Deep Learning. PhD by Publication Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/q7q7wPhD by Publication
Using machine learning based emulators for the sensitivity analysis of process-driven biophysical models
Johnston, David B.. 2022. Using machine learning based emulators for the sensitivity analysis of process-driven biophysical models. PhD Thesis Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/q7q78PhD Thesis
Development of Deep Learning Hybrid Models for Hydrological Predictions
Ahmed, Abul Abrar Masrur. 2022. Development of Deep Learning Hybrid Models for Hydrological Predictions. PhD by Publication Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/q7q5zPhD by Publication
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/10.1080/19942060.2021.1984992Article
A novel spectral entropy-based index for assessing the depth of anaesthesia
Ra, Jee Sook, Li, Tianning and Li, Yan. 2021. "A novel spectral entropy-based index for assessing the depth of anaesthesia." Brain Informatics. 8 (1). https://doi.org/10.1186/s40708-021-00130-8Article
Detection of k-complexes in EEG signals using a multi-domain feature extraction coupled with a least square support vector machine classifier
Al-Salman, Wessam, Li, Yan and Wen, Peng. 2021. "Detection of k-complexes in EEG signals using a multi-domain feature extraction coupled with a least square support vector machine classifier." Neuroscience Research. 172, pp. 26-40. https://doi.org/10.1016/j.neures.2021.03.012Article
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.2021.06.052Article
A preliminary study of the impact of lateral head orientations on the current distributions during tDCS
Song, Bo, Menezes de Oliveira, Marilia, Wang, Shuaifang, Li, Yan, Wen, Peng and Ahfock, Tony. 2019. "A preliminary study of the impact of lateral head orientations on the current distributions during tDCS." Liang, Peipeng, Goel, Vinod and Shan, Chunlei (ed.) 12th International Conference on Brain Informatics (BI 2019). Haikou, China 13 - 15 Dec 2019 Cham, Switzerland. https://doi.org/10.1007/978-3-030-37078-7_25Paper