Jinliang Ding

Jinliang Ding

Professor, Northeastern University

Publications

Selected journal papers

  1. Liu Y, Liu J, Ding J, et al. A surrogate-assisted differential evolution with knowledge transfer for expensive incremental optimization problems. IEEE Transactions on Evolutionary Computation, 2023. DOI: 10.1109/TEVC.2023.3291697
  2. Gao K, Yang C, Ding J, et al. Distributed Knowledge Transfer for Evolutionary Multitask Multimodal Optimization. IEEE Transactions on Evolutionary Computation, 2023. DOI: 10.1109/TEVC.2023.3291874
  3. Q Chen, J Ding, G Yen, S Yang, Multi-Population Evolution based Dynamic Constrained Multiobjective Optimization under Diverse Changing Environments, IEEE Transactions on Evolutionary Computation, 2023. DOI: 10.1109/TEVC.2023.3241762
  4. Z He, G Yen, J Ding, Knee Based Decision Making and Visualization in Many-Objective Optimization, IEEE Transactions on Evolutionary Computation, 2021, 25 (2), 292-306
  5. Q Chen, J Ding, S Yang, T Chai, A Novel Evolutionary Algorithm for Dynamic Constrained Multiobjective Optimization Problems, IEEE Transactions on Evolutionary Computation, 2020, 24 (4), 792 – 806
  6. C Yang, J Ding, Y Jin, T Chai, Off-line Data-driven Multi-objective Optimization: Knowledge Transfer between Surrogates and Generation of Final Solutions, IEEE Transactions on Evolutionary Computation, 2020, 24 (3), 409-423
  7. J Ding, C Yang, Y Jin, T Chai, Generalized Multi-tasking for Evolutionary Optimization of Expensive Problems, IEEE Transactions on Evolutionary Computation, 2019, 23 (1): 44 - 58.
  8. C Sun, Y Jin, R Cheng, J Ding, J Zeng, Surrogate-assisted Cooperative Swarm Optimization of High-dimensional Expensive Problems, IEEE Transactions on Evolutionary Computation, 2017, 21(4): 644 – 660.
  9. C Yang, Y Cheung, J Ding, KC Tan, Concept Drift-tolerant Transfer Learning in Dynamic Environments, IEEE Transactions on Neural Networks and Learning Systems, 2022, 33 (8), 3857-3871
  10. P Song, C Zhao, B Huang, J Ding, Explicit Representation and Customized Fault Isolation Framework for Learning Temporal and Spatial Dependencies in Industrial Processes, IEEE Transactions on Neural Networks and Learning Systems, 2023
  11. Li C, Ding J, Lewis F L, et al. Model-Free Q-Learning for the Tracking Problem of Linear Discrete-Time Systems[J]. IEEE Transactions on Neural Networks and Learning Systems, 2022.
  12. Yang C, Cheung Y M, Ding J, et al. Contrastive learning assisted-alignment for partial domain adaptation[J]. IEEE Transactions on Neural Networks and Learning Systems, 2022.
  13. Lu J, Ding J, Liu C, et al. Hierarchical-Bayesian-based sparse stochastic configuration networks for construction of prediction intervals[J]. IEEE Transactions on Neural Networks and Learning Systems, 2021, 33(8): 3560-3571.
  14. Li J, Ding J, Chai T, et al. Adaptive interleaved reinforcement learning: Robust stability of affine nonlinear systems with unknown uncertainty[J]. IEEE Transactions on Neural Networks and Learning Systems, 2020, 33(1): 270-280.
  15. Zheng N, Ding J, Chai T. DMGAN: Adversarial learning-based decision making for human-level plant-wide operation of process industries under uncertainties[J]. IEEE Transactions on Neural Networks and Learning Systems, 2020, 32(3): 985-998.
  16. Lu J, Ding J, Dai X, et al. Ensemble stochastic configuration networks for estimating prediction intervals: A simultaneous robust training algorithm and its application[J]. IEEE transactions on neural networks and learning systems, 2020, 31(12): 5426-5440.

Selected conference papers

  1. Zeli Zhao, Jinliang Ding, Jinxi Zhang, Distributed Optimal Coordination of Microgrid Systems over Unbalanced Digraph, 2022 First International Conference on Cyber-Energy Systems and Intelligent Energy (ICCSIE), 2023/1/14-15.
  2. Haoran Zhang, Chunhui Zhao, Jinliang Ding, Passivity-Based Online Reinforcement Learning for Real Time Model-Free Overhead Crane System Control, 2022 34th Chinese Control and Decision Conference (CCDC), 2022/08/15-17, 4116-4121.
  3. Jianfeng Zhang, Chunhui Zhao, Jinliang Ding, Youxian Sun, Xianling Li, Sparse Gaussian Feature Learning for Nonlinear Industrial Fault Diagnosis, 2022 34th Chinese Control and Decision Conference (CCDC), 2022/08/15-17, 540-545.
  4. Pengyu Song, Chunhui Zhao, Biao Huang, Jinliang Ding, Sparse Causality Analysis Approach with Time-varying Parameters for Root Cause Localization of Nonstationary Process, 2022 4th International Conference on Industrial Artificial Intelligence, 2022.8/24-27.
  5. Haofeng Wu, Jinliang Ding, Qingda Chen, Gaussian Process-assisted Evolutionary Algorithm for Constrained Expensive Multi-Objective Optimization, 2022 13th Asian Control Conference (ASCC), 2022/05/4-7, 1027-1032.
  6. Jiangtao Xu, Jinliang Ding, Qingda Chen, Ling Yi, Hot Rolling Scheduling of Heavy Plate Production Based on Heuristic and Ant Colony Algorithms, 2021 8th International Conference on Information, Cybernetics, and Computational Social Systems (ICCSS), 2021/12/10-12, 74-79.
  7. Pengyu Song, Chunhui Zhao, Jinliang Ding, Youxian Sun Xuanxuan Jin, Parallel Temporal and Spatial Modeling for Interpretable Fault Detection and Isolation of Industrial Processes, 2021 8th International Conference on Information, Cybernetics, and Computational Social Systems (ICCSS), 2021/12/10-12, 177-182.
  8. Yuandong Chen, Jinliang Ding, Discrete-time Scheduling Model of Entire Refinery with Multiscale Operation Time, 2021 3rd International Conference on Industrial Artificial Intelligence (IAI), 2021/11/08-11.
  9. Zhenfei Xiao, Jinna Li, Jinliang Ding, Shuai Liu, Guoliang Wang, Robust Optimal Tracking Control for Linear Systems via Adaptive Dynamic Programming method, 2020 IEEE 16th International Conference on Control & Automation (ICCA), 2020/10/09-11, 123-128.
  10. Qingda Chen, Qiang Liu, Jinliang Ding. An improved differential evolution algorithm for operating optimization of a distillation unit. Proceedings in the Chinese Automation Congress, 2019/11/22-24, 5277-5282.
  11. Chun Li, Jinliang Ding, Changxin Liu, Frank L. Lewis, A Novel On-line VI-ADP for Nonlinear Discrete-time Systems, 2019 IEEE 15th International Conference on Control and Automation (ICCA), 2019/07/16-19, 1314-1319.
  12. Zhenan He, Jinliang Ding, Robust Multi-objective Optimization with Less Computational Effort, 2019 1st International Conference on Industrial Artificial Intelligence (IAI), 2019/07/23-27.
  13. Qiang Liu, Jinliang Ding, Reference Vector Based Multidirectional Prediction for Evolutionary Dynamic Multiobjective Optimization, 2019 IEEE Congress on Evolutionary Computation (CEC), 2019/06/10-13,1081-1087.
  14. Ling Yi, Jinliang Ding, Changxin Liu, NMR principle analysis based object detection for intelligent measurement of crude oil moisture content, 2019 12th Asian Control Conference (ASCC), 2019/06/09-12, 456-461.
  15. Xue Xu, Qiang Liu, Jinliang Ding, Gasoline dry point prediction of fractionation processes using dynamic inner partial least squares, 2017 11th Asian Control Conference (ASCC), 2017/12/17-20, 1438-1442.