4611. Machine learning
| Title | 4611. Machine learning |
|---|---|
| Parent | 46. Information and Computing Sciences |
Latest research outputs
Sort by Date Title
Empirical curvelet transform based deep DenseNet model to predict NDVI using RGB drone imagery data
Diykh, Mohammed, Ali, Mumtaz, Jamei, Mehdi, Abdulla, Shahab, Uddin, Md Palash, Farooque, Aitazaz Ahsan, Labban, Abdulhaleem H. and Alabdally, Hussein. 2024. "Empirical curvelet transform based deep DenseNet model to predict NDVI using RGB drone imagery data." Computers and Electronics in Agriculture. 221. https://doi.org/10.1016/j.compag.2024.108964Article
FRAMU: Attention-based Machine Unlearning using Federated Reinforcement Learning
Shaik, Thanveer, Tao, Xiaohui, Li, Lin, Xie, Haoran, Cai, Taotao, Zhu, Xiaofeng and Li, Qing. 2024. "FRAMU: Attention-based Machine Unlearning using Federated Reinforcement Learning ." IEEE Transactions on Knowledge and Data Engineering. https://doi.org/10.1109/TKDE.2024.3382726Article
Short-term wind speed forecasting using an optimized three-phase convolutional neural network fused with bidirectional long short-term memory network model
Deo, Ravinesh C., Joseph, Lionel P., 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.2024.122624Article
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.2023.129938Article
Dynamic Task Allocation For Robotic Edge System Resilience Using Deep Reinforcement Learning
Afrin, Mahbuba, Jin, Jiong, Rahman, Ashfaqur, Li, Shi, Tian, Yu-Chuv and Li, Yan. 2024. "Dynamic Task Allocation For Robotic Edge System Resilience Using Deep Reinforcement Learning." IEEE Transactions on Systems, Man and Cybernetics: Systems. 54 (3), pp. 1438-1450. https://doi.org/10.1109/TSMC.2023.3327959Article
Digital strategies for nitrogen management in grain production systems: lessons from multi-method assessment using on-farm experimentation
Colaco, A.F., Whelan, B.M., Bramley, R.G.V., Richetti, J., Fajardo, M., McCarthy, A.C., Perry, E.M., Bender, A., Leo, S., Fitzgerald, G.J. and Lawes, R.A.. 2024. "Digital strategies for nitrogen management in grain production systems: lessons from multi-method assessment using on-farm experimentation ." Precision Agriculture. https://doi.org/10.1007/s11119-023-10102-zArticle
Quantitative improvement of streamflow forecasting accuracy in the Atlantic zones of Canada based on hydro-meteorological signals: A multi-level advanced intelligent expert framework
Jamei, Mozhdeh, Jamei, Mehdi, Ali, Mozhdeh, Karbasi, Masoud, Farooque, Aitazaz A., Malik, Anurag, Cheema, Saad Javed, Esau, Travis J. and Yaseen, Zaher Mundher. 2024. "Quantitative improvement of streamflow forecasting accuracy in the Atlantic zones of Canada based on hydro-meteorological signals: A multi-level advanced intelligent expert framework." Ecological Informatics. 80. https://doi.org/10.1016/j.ecoinf.2023.102455Article
Short-term drought Index forecasting for hot and semi-humid climate Regions: A novel empirical Fourier decomposition-based ensemble Deep-Random vector functional link strategy
Jamei, Mehdi, Ali, Mumtaz, Bateni, Sayed M., Jun, Changhyun, Karbasi, Masoud, Malik, Anurag, Jamei, Mozhdeh and Yaseen, Zaher Mundher. 2024. "Short-term drought Index forecasting for hot and semi-humid climate Regions: A novel empirical Fourier decomposition-based ensemble Deep-Random vector functional link strategy ." Computers and Electronics in Agriculture. 217. https://doi.org/1016/j.compag.2023.108609Article
Accurate monitoring of micronutrients in tilled potato soils of eastern Canada: Application of an eXplainable inspired-adaptive boosting framework coupled with SelectKbest
Jamei, Mehdi, Ali, Mumtaz, Afzaal, Hassan, Karbasi, Masoud, Malik, Anurag, Farooque, Aitazaz Ahsan, Haydar, Zeeshan and Zaman, Qamar Uz. 2024. "Accurate monitoring of micronutrients in tilled potato soils of eastern Canada: Application of an eXplainable inspired-adaptive boosting framework coupled with SelectKbest." Computers and Electronics in Agriculture. 216. https://doi.org/10.1016/j.compag.2023.108479Article
Application of an explainable glass-box machine learning approach for prognostic analysis of a biogas-powered small agriculture engine
Jamei, Mehdi, Sharma, Prabhakar, Ali, Mumtaz, Bora, Bhaskor J., Malik, Anurag, Paramasivam, Prabhu, Farooque, Aitazaz A. and Abdulla, Shahab. 2024. "Application of an explainable glass-box machine learning approach for prognostic analysis of a biogas-powered small agriculture engine." Energy. 288. https://doi.org/https://doi.org/10.1016/j.energy.2023.129862Article
Boruta extra tree-bidirectional long short-term memory model development for Pan evaporation forecasting: Investigation of arid climate condition
Karbasi, Masoud, Ali, Mumtaz, Bateni, Sayed M., Jun, Changhyun, Jamei, Mehdi and Yaseen, Zaher Mundher. 2024. "Boruta extra tree-bidirectional long short-term memory model development for Pan evaporation forecasting: Investigation of arid climate condition." Alexandria Engineering Journal. 86, pp. 425-442. https://doi.org/10.1016/j.aej.2023.11.061Article
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.2023.122059Article
Validation and Interpretation of a Multimodal Drowsiness Detection System Using Explainable Machine Learning
Hasan, Md Mahmudul, Watling, Christopher N. and Larue, Grégoire S.. 2024. "Validation and Interpretation of a Multimodal Drowsiness Detection System Using Explainable Machine Learning." Computer Methods and Programs in Biomedicine. 243. https://doi.org/10.1016/j.cmpb.2023.107925Article
Monthly sodium adsorption ratio forecasting in rivers using a dual interpretable glass-box complementary intelligent system: Hybridization of ensemble TVF-EMD-VMD, Boruta-SHAP, and eXplainable GPR
Jamei, Mehdi, Ali, Mumtaz, Karbasi, Masoud, Karimi, Bakhtiar, Jahannemaei, Neshat, Farooque, Aitazaz Ahsan and Yaseen, Zaher Mundher. 2024. "Monthly sodium adsorption ratio forecasting in rivers using a dual interpretable glass-box complementary intelligent system: Hybridization of ensemble TVF-EMD-VMD, Boruta-SHAP, and eXplainable GPR." Expert Systems with Applications. 237 (Part B). https://doi.org/10.1016/j.eswa.2023.121512Article
Evaluation and Prediction of Groundwater Quality for Irrigation Using an Integrated Water Quality Indices, Machine Learning Models and GIS Approaches: A Representative Case Study
Ibrahim, Hekmat, Yaseen, Zaher Mundher, Scholz, Miklas, Ali, Mumtaz, Gad, Mohamed, Elsayed, Salah, Khadr, Mosaad, Hussein, Hend, Ibrahim, Hazem H., Eid, Mohamed Hamdy, Kovács, Attila, Péter, Szűcs and Khalifa, Moataz M.. 2023. "Evaluation and Prediction of Groundwater Quality for Irrigation Using an Integrated Water Quality Indices, Machine Learning Models and GIS Approaches: A Representative Case Study." Water. 15 (4), pp. 1-26. https://doi.org/https://doi.org/10.3390/w15040694Article
Real-time epilepsy seizure detection based on EEG using tunable-Q wavelet transform and convolutional neural network
Shen, Mingkan, Wen, Peng, Song, Bo and Li, Yan. 2023. "Real-time epilepsy seizure detection based on EEG using tunable-Q wavelet transform and convolutional neural network." Biomedical Signal Processing and Control. 82. https://doi.org/10.1016/j.bspc.2022.104566Article
Artificial intelligence informed simulation of dissolved Inorganic Nitrogen from ungauged catchments to the Great Barrier Reef
O’Sullivan, Cherie. 2023. Artificial intelligence informed simulation of dissolved Inorganic Nitrogen from ungauged catchments to the Great Barrier Reef. PhD by Publication Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/z6206PhD by Publication
Revolutionizing healthcare with federated reinforcement learning: from machine learning to machine unlearning
Shaik, Thanveer Basha. 2023. Revolutionizing healthcare with federated reinforcement learning: from machine learning to machine unlearning. PhD by Publication Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/z6096PhD by Publication
Decentralized Blockchain Network
Abduljabbar, Tamara Abdulmunim, Tao, Xiaohui, Zhang, Ji, Yong, Jianming and Zhou, Xujuan. 2023. "Decentralized Blockchain Network." 2022 Tenth International Conference on Advanced Cloud and Big Data (CBD). Guilin, China 04 - 05 Nov 2022 China. IEEE (Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/CBD58033.2022.00049Paper
Multi-Method Approaches for Sleep EEG Analysis And Sleep Stage Classification
Zapata, Ignacio Alonso. 2023. Multi-Method Approaches for Sleep EEG Analysis And Sleep Stage Classification. PhD by Publication Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/z4yq2PhD by Publication
Deep learning based sleep stage classification
Ji, Xiaopeng. 2023. Deep learning based sleep stage classification. PhD by Publication Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/z4y9qPhD by Publication
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.. 2023. "Short-term wave power forecasting with hybrid multivariate variational mode decomposition model integrated with cascaded feedforward neural networks." Renewable Energy. 221. https://doi.org/https://doi.org/10.1016/j.renene.2023.119773Article
Hybridized artificial intelligence models with nature-inspired algorithms for river flow modeling: A comprehensive review, assessment, and possible future research directions
Tao, Hai, Abba, Sani I., Al-Areeq, Ahmed M., Tangang, Fredolin, Samantaray, Sandeep, Sahoo, Abinash, Siqueira, Hugo Valadares, Maroufpoor, Saman, Demir, Vahdettin, Bokde, Neeraj Dhanraj, Goliatt, Leonardo, Jamei, Mehdi, Ahmadianfar, Iman, Bhagat, Suraj Kumar, Halder, Bijay, Guo, Tianli, Helman, Daniel S., Ali, Mumtaz, Sattar, Sabaa, ..., Yaseen, Zaher Mundher. 2023. "Hybridized artificial intelligence models with nature-inspired algorithms for river flow modeling: A comprehensive review, assessment, and possible future research directions ." Engineering Applications of Artificial Intelligence. 129. https://doi.org/10.1016/j.engappai.2023.107559Article
Development of an enhanced bidirectional recurrent neural network combined with time-varying filter-based empirical mode decomposition to forecast weekly reference evapotranspiration
Karbasi, Masoud, Jamei, Mehdi, Ali, Mumtaz, Malik, Anurag, Chu, Xuefeng, Farooque, Aitazaz Ahsan and Yaseen, Zaher Mundher. 2023. "Development of an enhanced bidirectional recurrent neural network combined with time-varying filter-based empirical mode decomposition to forecast weekly reference evapotranspiration." Agricultural Water Management. 290. https://doi.org/https://doi.org/10.1016/j.agwat.2023.108604Article
Bathymetric modelling for long-term monitoring of water dynamics of Ramsar-listed lakes using inundation frequency and photon-counting LiDAR data
Zhang, Zhenyu and Liu, Xiaoye. 2023. "Bathymetric modelling for long-term monitoring of water dynamics of Ramsar-listed lakes using inundation frequency and photon-counting LiDAR data." Ecohydrology and Hydrobiology. https://doi.org/10.1016/j.ecohyd.2023.10.003Article
Adaptive Regularization and Resilient Estimation in Federated Learning
Uddin, Md Palash, Xiang, Yong, Zhao, Yao, Ali, Mumtaz, Zhang, Yushu and Gao, Longxiang. 2023. "Adaptive Regularization and Resilient Estimation in Federated Learning." IEEE Transactions on Services Computing. https://doi.org/10.1109/TSC.2023.3332703Article
An ensemble machine learning-based intelligent system for human activity recognition using sensory data
Abdulla, Shahab, Diykh, Mohammed, Siuly, Siuly and Ali, Mumtaz. 2023. "An ensemble machine learning-based intelligent system for human activity recognition using sensory data." Sinha, G.R., Subudhi, Bidyadhar, Fan, Chih-Peng and Nisar, Humaira (ed.) Cognitive Sensing Technologies and Applications. Institution of Engineering and Technology (IET). pp. 119-130Edited book (chapter)
Query2Trip: Dual-Debiased Learning for Neural Trip Recommendation
Wang, Peipei, Li, Lin, Wang, Ru and Tao, Xizohui. 2023. "Query2Trip: Dual-Debiased Learning for Neural Trip Recommendation." 28th International Conference on Database Systems for Advanced Applications (DASFAA 2023). Tianjin, China 17 - 20 Apr 2023 Switzerland . Springer. pp. 80-96 https://doi.org/10.1007/978-3-031-30672-3_6Paper
Hyperbolic Mutual Learning for Bundle Recommendation
Ke, Haole, Li, Lin, Wang, PeiPei, Yuan, Jingling and Tao, Xiaohui. 2023. "Hyperbolic Mutual Learning for Bundle Recommendation." 28th International Conference on Database Systems for Advanced Applications (DASFAA 2023). Tianjin, China 17 - 20 Apr 2023 Switzerland . Springer. https://doi.org/10.1007/978-3-031-30672-3_28Paper
Contribution of Geometric Feature Analysis for Deep Learning Classification Algorithms of Urban LiDAR Data
Tarsha Kurdi, Fayez, Amakhchan, Wijdan, Gharineiat, Zahra, Boulaassal, Hakim and Kharki, Omar El. 2023. "Contribution of Geometric Feature Analysis for Deep Learning Classification Algorithms of Urban LiDAR Data." Sensors. 23 (17). https://doi.org/10.3390/s23177360Article
Dual-interactive fusion for code-mixed deep representation learning in tag recommendation
Li, Lin, Wang, Peipei, Zheng, Xinhao, Xie, Qing, Tao, Xiaohui and Velasquez, Juan D.. 2023. "Dual-interactive fusion for code-mixed deep representation learning in tag recommendation." Information Fusion. 99. https://doi.org/10.1016/j.inffus.2023.101862Article
3DSleepNet: A Multi-Channel Bio-Signal Based Sleep Stages Classification Method Using Deep Learning
Ji, Xiaopeng, Li, Yan and Wen, Peng. 2023. "3DSleepNet: A Multi-Channel Bio-Signal Based Sleep Stages Classification Method Using Deep Learning." IEEE Transactions on Neural Systems and Rehabilitation Engineering. 31, pp. 3513-3523. https://doi.org/10.1109/TNSRE.2023.3309542Article
Early detection of paediatric and adolescent obsessive–compulsive, separation anxiety and attention deficit hyperactivity disorder using machine learning algorithms
Haque, Umme Marzia, Kabir, Enamul and Khanam, Rasheda. 2023. "Early detection of paediatric and adolescent obsessive–compulsive, separation anxiety and attention deficit hyperactivity disorder using machine learning algorithms." Health Information Science and Systems. 11 (1), pp. 1-14. https://doi.org/10.1007/s13755-023-00232-zArticle
New achievements on daily reference evapotranspiration forecasting: Potential assessment of multivariate signal decomposition schemes
Ali, Mumtaz, Jamei, Mehdi, Prasad, Ramendra, Karbasi, Masoud, Xiang, Yong, Cai, Borui, Abdulla, Shahab, Farooque, Aitazaz Ahsan and Labban, Abdulhaleem H.. 2023. "New achievements on daily reference evapotranspiration forecasting: Potential assessment of multivariate signal decomposition schemes." Ecological Indicators. 155. https://doi.org/10.1016/j.ecolind.2023.111030Article
Automatic identification of schizophrenia based on EEG signals using dynamic functional connectivity analysis and 3D convolutional neural network
Shen, Mingkan, Wen, Peng, Song, Bo and Li, Yan. 2023. "Automatic identification of schizophrenia based on EEG signals using dynamic functional connectivity analysis and 3D convolutional neural network." Computers in Biology and Medicine. 160. https://doi.org/10.1016/j.compbiomed.2023.107022Article
Prediction of Water Quality in Reservoirs: A Comparative Assessment of Machine Learning and Deep Learning Approaches in the Case of Toowoomba, Queensland, Australia
Farzana, Syeda Zehan, Paudyal, Dev Raj, Chadalavada, Sreeni and Alam, Md Jahangir. 2023. "Prediction of Water Quality in Reservoirs: A Comparative Assessment of Machine Learning and Deep Learning Approaches in the Case of Toowoomba, Queensland, Australia." Geosciences. 13 (293). https://doi.org/10.3390/geosciences13100293Article
Mental stress recognition on the fly using neuroplasticity spiking neural networks
Weerasinghe, Mahima Milinda Alwis, Wang, Grace, Whalley, Jacqueline and Crook-Rumsey, Mark. 2023. "Mental stress recognition on the fly using neuroplasticity spiking neural networks." Scientific Reports. 13. https://doi.org/10.1038/s41598-023-34517-wArticle
Multivariate data decomposition based deep learning approach to forecast one-day ahead significant wave height for ocean energy generation
Zheng, Zihao, Ali, Mumtaz, Jamei, Mehdi, Xiang, Yong, Abdulla, Shahab, Yaseen, Zaher Mundher and Farooque, Aitazaz A.. 2023. "Multivariate data decomposition based deep learning approach to forecast one-day ahead significant wave height for ocean energy generation." Renewable and Sustainable Energy Reviews. 185. https://doi.org/https://doi.org/10.1016/j.rser.2023.113645Article
Multitask Learning From Augmented Auxiliary Data for Improving Speech Emotion Recognition
Latif, Siddique, Rana, Rajib, Khalifa, Sara, Jurdak, Raja and Schuller, Bjorn W.. 2023. "Multitask Learning From Augmented Auxiliary Data for Improving Speech Emotion Recognition ." IEEE Transactions on Affective Computing. 14 (4), pp. 3164-3176. https://doi.org/10.1109/TAFFC.2022.3221749Article
Designing a decomposition-based multi-phase pre-processing strategy coupled with EDBi-LSTM deep learning approach for sediment load forecasting
Jamei, Mehdi, Ali, Mumtaz, Malik, Anurag, Rai, Priya, Karbasi, Masoud, Farooque, Aitazaz A. and Yaseen, Zaher Mundher. 2023. "Designing a decomposition-based multi-phase pre-processing strategy coupled with EDBi-LSTM deep learning approach for sediment load forecasting." Ecological Indicators. 153. https://doi.org/https://doi.org/10.1016/j.ecolind.2023.110478Article