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Convergence analysis of online gradient method for BP neural networks W Wu, J Wang, M Cheng, Z Li Neural Networks 24 (1), 91-98, 2011 | 196 | 2011 |
Feature selection for neural networks using group lasso regularization H Zhang, J Wang, Z Sun, JM Zurada, NR Pal IEEE Transactions on Knowledge and Data Engineering 32 (4), 659-673, 2020 | 168 | 2020 |
Fractional-order gradient descent learning of BP neural networks with Caputo derivative J Wang, Y Wen, Y Gou, Z Ye, H Chen Neural networks 89, 19-30, 2017 | 165 | 2017 |
Affine transformation-enhanced multifactorial optimization for heterogeneous problems X Xue, K Zhang, KC Tan, L Feng, J Wang, G Chen, X Zhao, L Zhang, ... IEEE Transactions on Cybernetics 52 (7), 6217-6231, 2022 | 159 | 2022 |
Application of extreme learning machine and neural networks in total organic carbon content prediction in organic shale with wire line logs X Shi, J Wang, G Liu, L Yang, X Ge, S Jiang Journal of Natural Gas Science and Engineering 33, 687-702, 2016 | 129 | 2016 |
History matching of naturally fractured reservoirs using a deep sparse autoencoder K Zhang, J Zhang, X Ma, C Yao, L Zhang, Y Yang, J Wang, J Yao, H Zhao SPE Journal 26 (04), 1700-1721, 2021 | 124 | 2021 |
Data-driven niching differential evolution with adaptive parameters control for history matching and uncertainty quantification X Ma, K Zhang, L Zhang, C Yao, J Yao, H Wang, W Jian, Y Yan Spe Journal 26 (02), 993-1010, 2021 | 107 | 2021 |
An enhanced competitive swarm optimizer with strongly convex sparse operator for large-scale multiobjective optimization X Wang, K Zhang, J Wang, Y Jin IEEE transactions on evolutionary computation 26 (5), 859-871, 2022 | 106 | 2022 |
Training effective deep reinforcement learning agents for real-time life-cycle production optimization K Zhang, Z Wang, G Chen, L Zhang, Y Yang, C Yao, J Wang, J Yao Journal of Petroleum Science and Engineering 208, 109766, 2022 | 102 | 2022 |
A novel pruning algorithm for smoothing feedforward neural networks based on group lasso method J Wang, C Xu, X Yang, JM Zurada IEEE transactions on neural networks and learning systems 29 (5), 2012-2024, 2018 | 98 | 2018 |
An Efficient Approach for Real‐Time Prediction of Rate of Penetration in Offshore Drilling X Shi, G Liu, X Gong, J Zhang, J Wang, H Zhang Mathematical Problems in Engineering 2016 (1), 3575380, 2016 | 97 | 2016 |
Feature selection using a neural network with group lasso regularization and controlled redundancy J Wang, H Zhang, J Wang, Y Pu, NR Pal IEEE transactions on neural networks and learning systems 32 (3), 1110-1123, 2021 | 94 | 2021 |
Multifidelity genetic transfer: an efficient framework for production optimization F Yin, X Xue, C Zhang, K Zhang, J Han, BX Liu, J Wang, J Yao Spe Journal 26 (04), 1614-1635, 2021 | 86 | 2021 |
Batch gradient method with smoothing L1/2 regularization for training of feedforward neural networks W Wu, Q Fan, JM Zurada, J Wang, D Yang, Y Liu Neural Networks 50, 72-78, 2014 | 80 | 2014 |
An adaptive neuro-fuzzy system with integrated feature selection and rule extraction for high-dimensional classification problems G Xue, Q Chang, J Wang, K Zhang, NR Pal IEEE Transactions on Fuzzy Systems 31 (7), 2167-2181, 2023 | 77 | 2023 |
A recalling-enhanced recurrent neural network: Conjugate gradient learning algorithm and its convergence analysis T Gao, X Gong, K Zhang, F Lin, J Wang, T Huang, JM Zurada Information Sciences 519, 273-288, 2020 | 68 | 2020 |
Efficient hierarchical surrogate-assisted differential evolution for high-dimensional expensive optimization G Chen, Y Li, K Zhang, X Xue, J Wang, Q Luo, C Yao, J Yao Information Sciences 542, 228-246, 2021 | 67 | 2021 |
Learning Optimized Structure of Neural Networks by Hidden Node Pruning With L₁ Regularization X Xie, H Zhang, J Wang, Q Chang, J Wang, NR Pal IEEE transactions on cybernetics 50 (3), 1333-1346, 2020 | 60* | 2020 |
Deterministic convergence of conjugate gradient method for feedforward neural networks J Wang, W Wu, JM Zurada Neurocomputing 74 (14-15), 2368-2376, 2011 | 59 | 2011 |