| A semi-supervised Laplacian extreme learning machine and feature fusion with CNN for industrial superheat identification Y Lei, X Chen, M Min, Y Xie Neurocomputing 381, 186-195, 2020 | 53 | 2020 |
| A novel self-supervised deep LSTM network for industrial temperature prediction in aluminum processes application Y Lei, HR Karimi, X Chen Neurocomputing 502, 177-185, 2022 | 36 | 2022 |
| Processes soft modeling based on stacked autoencoders and wavelet extreme learning machine for aluminum plant-wide application Y Lei, HR Karimi, L Cen, X Chen, Y Xie Control Engineering Practice 108, 104706, 2021 | 36 | 2021 |
| A scoping review on monitoring mental health using smart wearable devices N Long, Y Lei, L Peng, P Xu, P Mao Math. Biosci. Eng 19 (8), 7899-7919, 2022 | 35 | 2022 |
| A hybrid regularization semi-supervised extreme learning machine method and its application Y Lei, L Cen, X Chen, Y Xie IEEE Access 7, 30102-30111, 2019 | 16 | 2019 |
| An improved cell situation identification approach with convolutional neural network and wavelet extreme learning machine Y Lei, X Chen, Y Xie Proceedings of the Institution of Mechanical Engineers, Part I: Journal of …, 2021 | 8 | 2021 |
| A self-supervised temporal temperature prediction method based on dilated contrastive learning Y Lei, X Chen, Y Xie, L Cen Journal of Process Control 120, 150-158, 2022 | 6 | 2022 |
| Hessian Regularization Semi-supervised Extreme Learning Machine for Superheat Identification in Aluminum Reduction Cell Y Lei, X Chen, W Gui 2019 Chinese Control And Decision Conference (CCDC), 4406-4411, 2019 | 4 | 2019 |
| Intelligent optimal framework for the industrial mining plant-wide prediction control Y Lei IEEE Transactions on Instrumentation and Measurement 72, 1-12, 2023 | 3 | 2023 |
| Manifold semi-supervised learning for aluminum electrolysis temperature identification based on regularized hierarchical extreme learning machine Y Lei, F Liu, HR Karimi, X Chen Proceedings of the Institution of Mechanical Engineers, Part I: Journal of …, 2022 | 3 | 2022 |
| A novel superheat identification of aluminum electrolysis with kernel semi-supervised extreme learning machine Y Jiang, P Li, Y Lei Journal of Physics: Conference Series 1631 (1), 012005, 2020 | 3 | 2020 |
| A novel kernel-based extreme learning machine with incremental hidden layer nodes M Min, X Chen, Y Lei, Z Chen, Y Xie IFAC-PapersOnLine 53 (2), 11836-11841, 2020 | 3 | 2020 |
| DualLSTM: A novel key-quality prediction for a hierarchical cone thickener Y Lei, HR Karimi Control Engineering Practice 137, 105566, 2023 | 2 | 2023 |
| A Digital Twin Model of Three-Dimensional Shading for Simulation of the Ironmaking Process Y Lei, HR Karimi Machines 10 (12), 1122, 2022 | 2 | 2022 |
| A wave forecasting method based on probabilistic diffusion LSTM network for model predictive control of wave energy converters Y Lei Applied Soft Computing, 112006, 2024 | | 2024 |
| Underflow concentration prediction based on improved dual bidirectional LSTM for hierarchical cone thickener system Y Lei, HR Karimi The International Journal of Advanced Manufacturing Technology 127 (3), 1651 …, 2023 | | 2023 |
| A Digital Twin Model of Three-Dimensional Shading for Simulation of the Blast Furnace Ironmaking Process. Machines 2022, 10, 1122 Y Lei, HR Karimi s Note: MDPI stays neutral with regard to jurisdictional claims in published …, 2022 | | 2022 |
| A self-supervised LSTM network for cell temperature prediction in aluminium electrolysis reduction Y Lei, HR Karimi 18th International Conference on Condition Monitoring and Asset Management …, 2022 | | 2022 |
Yongfang XIESchool of Information Science and Engineering, Central South University在 csu.edu.cn 的电子邮件经过验证
Yongfang XIESchool of Information Science and Engineering, Central South University在 csu.edu.cn 的电子邮件经过验证
zhiwen chenCentral South university在 csu.edu.cn 的电子邮件经过验证