| DTDR–ALSTM: Extracting dynamic time-delays to reconstruct multivariate data for improving attention-based LSTM industrial time series prediction models J Li, B Yang, H Li, Y Wang, C Qi, Y Liu Knowledge-Based Systems 211, 106508, 2021 | 46 | 2021 |
| A novel intelligent modeling framework integrating convolutional neural network with an adaptive time-series window and its application to industrial process operational … Y Wang, H Li Chemometrics and Intelligent Laboratory Systems 179, 64-72, 2018 | 35 | 2018 |
| Capacity estimation of lithium-ion batteries based on data aggregation and feature fusion via graph neural network Z Wang, F Yang, Q Xu, Y Wang, H Yan, M Xie Applied Energy 336, 120808, 2023 | 21 | 2023 |
| Operational trend prediction and classification for chemical processes: A novel convolutional neural network method based on symbolic hierarchical clustering Y Wang, Y Zhang, Z Wu, H Li, PD Christofides Chemical Engineering Science 225, 115796, 2020 | 20 | 2020 |
| Industrial time-series modeling via adapted receptive field temporal convolution networks integrating regularly updated multi-region operations based on PCA Y Wang, K Yang, H Li Chemical Engineering Science 228, 115956, 2020 | 19 | 2020 |
| Computational fluid dynamics-based in-situ sensor analytics of direct metal laser solidification process using machine learning YM Ren, Y Zhang, Y Ding, Y Wang, PD Christofides Computers & Chemical Engineering 143, 107069, 2020 | 19 | 2020 |
| Multi-criteria spare parts classification using the deep convolutional neural network method K Yang, Y Wang, S Fan, A Mosleh Applied sciences 11 (15), 7088, 2021 | 17 | 2021 |
| Industrial process time-series modeling based on adapted receptive field temporal convolution networks concerning multi-region operations Y Wang, H Li Computers & Chemical Engineering 139, 106877, 2020 | 13 | 2020 |
| An adaptive mode convolutional neural network based on bar-shaped structures and its operation modeling to complex industrial processes Y Wang, H Li, C Qi Chemometrics and Intelligent Laboratory Systems 199, 103932, 2020 | 13 | 2020 |
| Furnace thermal efficiency modeling using an improved convolution neural network based on parameter-adaptive mnemonic enhancement optimization Y Wang, J Huang, C Su, H Li Applied Thermal Engineering 149, 332-343, 2019 | 12 | 2019 |
| Remaining useful life prediction via long‐short time memory neural network with novel partial least squares and genetic algorithm K Yang, Y Wang, Y Yao, S Fan Quality and Reliability Engineering International 37 (3), 1080-1098, 2021 | 11 | 2021 |
| An improved bar-shaped sliding window CNN tailored to industrial process historical data with applications in chemical operational optimizations Y Wang, H Li, J Huang, C Su, B Yang, C Qi Industrial & Engineering Chemistry Research 58 (47), 21219-21232, 2019 | 10 | 2019 |
| Adapted receptive field temporal convolutional networks with bar-shaped structures tailored to industrial process operation models Y Wang, Y Zhang, H Li Industrial & Engineering Chemistry Research 59 (13), 5482-5490, 2020 | 9 | 2020 |
| A novel bidirectional DiPLS based LSTM algorithm and its application in industrial process time series prediction Y Wang, D Bao, SJ Qin Chemometrics and Intelligent Laboratory Systems 240, 104878, 2023 | 6 | 2023 |
| Modeling of furnace operation with a new adaptive data echo state network method integrating block recursive partial least squares Y Wang, H Li, B Yang Applied Thermal Engineering 171, 115088, 2020 | 6 | 2020 |
| Complex chemical process operation evaluations using a novel analytic hierarchy process model integrating deep residual network with principal component analysis Y Wang, H Li Chemometrics and Intelligent Laboratory Systems 191, 118-128, 2019 | 6 | 2019 |
| Attention-mechanism based DiPLS-LSTM and its application in industrial process time series big data prediction Y Wang, C Qian, SJ Qin Computers & Chemical Engineering 176, 108296, 2023 | 5 | 2023 |
| Symbolic multivariable hierarchical clustering based convolutional neural networks with applications in industrial process operating trend predictions Y Wang, YM Ren, H Li Industrial & Engineering Chemistry Research 59 (34), 15133-15145, 2020 | 5 | 2020 |
| Hybrid cycle reservoir with jumps for multivariate time series prediction: industrial application in oil drilling process J Li, H Li, Y Wang, B Yang, C Qi, L Li Measurement Science and Technology 31 (1), 015103, 2019 | 5 | 2019 |
| Complex Chemical Process Evaluation Methods Using a New Analytic Hierarchy Process Model Integrating Deep Residual Network with Multiway Principal Component Analysis Y Wang, H Li Industrial & Engineering Chemistry Research 58 (31), 13889-13899, 2019 | 5 | 2019 |
Yichi ZhangUCLAVerified email at g.ucla.edu
