460207. Modelling and simulation
| Title | 460207. Modelling and simulation |
|---|---|
| Parent | 4602. Artificial intelligence |
Latest research outputs
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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
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
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-xArticle
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/s41598-021-96751-4Article
An integrated systems model for sustainable agricultural development under changing climate: a case study in a coffee production system in Viet Nam
Pham, Yen Hoang. 2021. An integrated systems model for sustainable agricultural development under changing climate: a case study in a coffee production system in Viet Nam. PhD Thesis Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/dbty-kn67PhD Thesis
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/rs13040554Article
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/s00477-021-01969-3Article
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.2020.102005Article
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.2021.126350Article
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.2021.106158Article
Stroke Classification in Simulated Electromagnetic Imaging Using Graph Approaches
Zhu, Guohun, Bialkowski, Alina, Guo, Lei, Mohammed, Beadaa and Abbosh, Amin. 2021. "Stroke Classification in Simulated Electromagnetic Imaging Using Graph Approaches ." IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology. 5 (1), pp. 46-53. https://doi.org/10.1109/JERM.2020.2995329Article
Multiscale entropy algorithms and their applications in cardiac disease discrimination
Wan, Xiangkui, Zhu, Binru, Jin, Zhiyao, Zhang, Mingru and Li, Yan. 2020. "Multiscale entropy algorithms and their applications in cardiac disease discrimination." Journal of Mechanics in Medicine and Biology. 20 (8), pp. 1-13. https://doi.org/10.1142/S0219519420500529Article
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.2020.3039002Article
Functional-structural plant models mission in advancing crop science: opportunities and prospects
Soualiou, Soualihou, Wang, Zhiwei, Sun, Weiwei, de Reffye, Philippe, Collins, Brian, Louarn, Gaëtan and Song, Youhong. 2021. "Functional-structural plant models mission in advancing crop science: opportunities and prospects." Frontiers in Plant Science. 12. https://doi.org/10.3389/fpls.2021.747142Article
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. 391-436Edited book (chapter)
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/s00477-020-01918-6Article
Brain network, modelling and corresponding EEG patterns for health and disease states
Al-Hossenat, Auhood Hadi Jabbar. 2020. Brain network, modelling and corresponding EEG patterns for health and disease states. PhD Thesis Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/7xxq-3k23PhD Thesis
Probabilistic and artificial intelligence modelling of drought and agricultural crop yield in Pakistan
Ali, Mumtaz. 2019. Probabilistic and artificial intelligence modelling of drought and agricultural crop yield in Pakistan. PhD Thesis Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/S847-M467PhD Thesis
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. 359-381Edited book (chapter)
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. 293-357Edited book (chapter)
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. 281-292Edited book (chapter)
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. 29-47Edited book (chapter)
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.Edited book
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.2020.110003Article
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/en13092307Article