Modeling the hydrocracking process with deep neural networks W Song, V Mahalec, J Long, M Yang, F Qian Industrial & Engineering Chemistry Research 59 (7), 3077-3090, 2020 | 34 | 2020 |
Adaptive weighted hybrid modeling of hydrocracking process and its operational optimization W Song, W Du, C Fan, M Yang, F Qian Industrial & Engineering Chemistry Research 60 (9), 3617-3632, 2021 | 14 | 2021 |
Deep Bayesian slow feature extraction with application to industrial inferential modeling C Jiang, Y Lu, W Zhong, B Huang, D Tan, W Song, F Qian IEEE Transactions on Industrial Informatics 19 (1), 40-51, 2021 | 13 | 2021 |
A new lumped kinetic model of an industrial hydrocracking process W Song, W Zhong, M Yang, W Du, F Qian Chemical engineering transactions 61, 673-678, 2017 | 10 | 2017 |
Searching for robustness intervals in evolutionary robust optimization W Du, W Song, Y Tang, Y Jin, F Qian IEEE transactions on evolutionary computation 26 (1), 58-72, 2021 | 8 | 2021 |
A novel path-based reproduction operator for multi-objective optimization W Song, W Du, C Fan, W Zhong, F Qian Swarm and Evolutionary Computation 59, 100741, 2020 | 5 | 2020 |
An improved weighted optimization approach for large-scale global optimization M Chen, W Du, W Song, C Liang, Y Tang Complex & Intelligent Systems 8 (2), 1259-1280, 2022 | 3 | 2022 |