郑州大学计算智能实验室

Computational Intelligence Laboratory

期刊论文

The papers here are for faster dissemination and academic research convinence purpose only, and the copyright of the final papers belongs to the corresponding publishers !

‖ 2023

  • Y. X. Li, J Liang, C. T. Yue, K. J. Yu, H Guo. An incremental random walk algorithm for sampling continuous fitness landscapes[J]. Neurocomputing, 2023: 126549. IF: 5.779, 中科院二区.  (paper)

  • J Liang, H Guo, K Chen, K. J. Yu, C. T. Yue, Y. P. Ma. A Survey on Intelligent Optimization Approaches to Boiler Combustion Optimization[J]. CAAI Artificial Intelligence Research, 2023, doi: 10.26599/AIR.2023.91

    50014.  (paper)

  • K. J. Yu, D. Z. Zhang, J. Liang*, B. Y. Qu, M. N. Liu, K. Chen, C. T. Yue, L. Wang. A Framework Based on Historical Evolution Learning for Dynamic Multiobjective Optimization[J]. IEEE Transactions on Evolutionary Computation, 2023, doi: 10.1109/TEVC.2023.3290485. IF: 16.497, 中科院一区.  (paper)(code)

  • J. Liang, Y. Y. Zhang, B. Y. Qu, K. Chen, K. J. Yu and C. T. Yue. A Multiform Optimization Framework for Multi-objective Feature Selection in Classification. IEEE Transactions on Evolutionary Computation. 2023. IF: 16.497, 中科院一区. (paper)(code)

  • Ying Bi, Jing Liang*, Bing Xue, Mengjie Zhang. A Genetic Programming Approach with Building Block Evolving and Reusing to Image Classification. IEEE Transactions on Evolutionary Computation, 2023. IF: 16.497, 中科院一区. (paper)

  • K. J. Qiao, J. Liang*, K. J. Yu, C. T. Yue, H. Y. Lin, D. Z. Zhang, B. Y. Qu. Evolutionary constrained multiobjective optimization: scalable high-dimensional constraint benchmarks and algorithm[J]. IEEE Transactions on Evolutionary Computation, 2023. Doi: 10.1109/TEVC.2023.3281666. IF: 16.497, 中科院一区. (paper)(code)

  • K. J. Qiao, J. Liang*, Z. Y. Liu, K. J. Yu, C. T. Yue, B. Y. Qu. Evolutionary multitasking with global and local auxiliary tasks for constrained multi-objective optimization[J]. IEEE/CAA Journal of Automatica Sinica, 2023. Doi: 10.1109/JAS.2023.123336. IF: 7.847, 中科院一区. (paper)(code)

  • J. Liang, K Li, K. J. Yu, C. T. Yue*, Y. X. Li, H. Song. A novel differential evolution algorithm based on local fitness landscape information for optimization problems[J]. IEICE TRANSACTIONS on Information and Systems, 2023, E106-D(5): 601-616. IF: 0.695, 中科院四区. (paper)

  • J. Liang, Z. L. Chen, Y. N. Wang, X. X. Ban*, K. J. Qiao, K. J. Yu. A dual-population constrained multi-objective evolutionary algorithm with variable auxiliary population size[J]. Complex & Intelligent Systems, 2023. IF: 6.700, 中科院二区. (paper)

  • Y. X. Li, J. Liang*, K. J. Yu, C. T. Yue, Y. J. Zhang. Keenness for characterizing continuous optimization problems and predicting differential evolution algorithm performance[J]. Complex & Intelligent Systems, 2023: 1-16. IF: 6.700, 中科院二区.  (paper)

  • P. Wang, B. Xue, J. Liang*, M. J. Zhang. Feature Clustering-Assisted Feature Selection with Differential Evolution[J]. Pattern Recognition, 2023, 140: 109523. IF: 8.518, 中科院一区. (paper)

  • P. Wang, B. Xue, J. Liang, M. J. Zhang. Feature Selection Using Diversity-Based Multi-objective Binary Differential Evolution[J]. Information Sciences, 2023. IF: 8.233, 中科院一区. (paper)

  • Z Wu, M Yu*, J.Liang. Parameter optimization of energy-efficient antenna system using period-based memetic algorithm. Expert Systems with Applications. 2023, 214: 119131. IF: 8.665, 中科院一区. (paper)

  • L. Yan, W. L. Qi, A. K. Qin, S. X. Yang, D. W. Gong, B. Y. Qu*, J. J. Liang. Manifold clustering-based prediction for dynamic multiobjective optimization [J]. Swarm and Evolutionary Computation, 2023, 77:101254 . IF: 10.267, 中科院一区. (paper)(code)

  • L. Yan, W. L. Qi, J. J. Liang, B. Y. Qu*, K. J. Yu, C. T. Yue, X. Z. Chai. Inter-individual correlation and Dimension Based Dual Learning for Dynamic Multi-objective Optimization [J]. IEEE Transactions on Evolutionary Computation, 2023. Doi: 10.1109/TEVC.2023.3235196. IF: 16.497, 中科院一区. (paper)(code)

  • K. J. Qiao, J. Liang*, K. J. Yu, M. H. Wang, B. Y. Qu, C. T. Yue, Y. N. Guo. A Self-Adaptive Evolutionary Multi-Task Based Constrained Multi-Objective Evolutionary Algorithm [J]. IEEE Transactions on Emerging Topics in Computational Intelligence, 2023. Doi: 10.1109/TETCI.2023.3236633. IF: 4.851, 中科院二区. (paper)(code)

  • H. S. Wang, Y. Zhang, J. Liang*, et al. DAFA-BiLSTM: Deep Autoregression Feature Augmented Bidirectional LSTM network for time series prediction[J]. Neural Networks, 2023, 157: 240-256. IF: 9.657, 中科院二区. (paper)



‖ 2022

  • J. Liang, X. X. Ban, K. J. Yu*, K. J. Qiao, B. Y. Qu. Constrained multiobjective differential evolution algorithm with infeasible-proportion control mechanism[J]. Knowledge-Based Systems, 2022, 250: 109105. IF: 8.139, 中科院一区. (paper)

  • Y. N. Guo, G. Y. Chen, M. Jiang, D. W. Gong, J. Liang*. A Knowledge guided Transfer Strategy for Evolutionary Dynamic Multiobjective Optimization [J]. IEEE Transactions on Evolutionary Computation, 2022. Doi: 10.1109/TEVC.2022.3222844. IF: 16.497, 中科院一区. (paper)

  • Y. X. Li, K. J. Yu, J. Liang*, C. T. Yue, K. J. Qiao. A landscape-aware particle swarm optimization for parameter identification of photovoltaic models [J]. Applied Soft Computing, 2022,131: 109793. IF: 8.263, 中科院二区. (paper)(code)

  • D. Yang, L. Wang, K. J. Yu, J. Liang*. A reinforcement learning-based energy management strategy for fuel cell hybrid vehicle considering real-time velocity prediction [J]. Energy Conversion and Management, 2022, 274: 116453. IF: 11.553, 中科院一区. (paper)

  • J. Liang, B. Y. Qu, B. L. Li, K. J. Yu, and C. T. Yue. Locating multiple roots of nonlinear equation systems via multi-strategy optimization algorithm with sequence quadratic program[J]. Science China Information Sciences, 2022, 65(7): 1-3. IF: 7.275, 中科院二区. (paper) 

  • J. Liang, H. Guo, K. Chen*, K. J. Yu, C. T. Yue, X. Li. An improved Kalman particle swarm optimization for modeling and optimizing of boiler combustion characteristics[J]. Robotica, 2022: 1-11. IF: 2.406, 中科院三区. (paper)(code)

  • Y. X. Li, J. Liang*, K. J. Yu, K. Chen, Y. N. Guo, C. T. Yue, L. Y. Zhang. Adaptive Local Landscape Feature Vector for Problem Classification and Algorithm Selection[J]. Applied Soft Computing, 2022, 131: 109751. IF: 8.263, 中科院二区. (paper)(code)

  • J. J. Liang, Z. W. Li, C. T. Yue, Z. Hu, H. Cheng, Z. X. Liu, W. F. Guo*. Multi-modal Optimization to Identify Personalized Biomarkers for Disease Prediction of Individual Patients with Cancer [J]. Briefings in Bioinformatics, 2022, 23(5). IF: 13.994, 中科院一区. (paper)

  • J. J. Liang, H. Y.  Lin, C. T. Yue*, K. J.  Yu, Y. Guo and K. J. Qiao, Multiobjective Differential Evolution with Speciation for Constrained Multimodal Multiobjective Optimization [J]. IEEE Transactions on Evolutionary Computation, 2022, Doi: 10.1109/TEVC.2022.3194253. IF: 16.497, 中科院一区.(paper)(code)

  • K. J. Yu, D. Z. Zhang, J. J. Liang, K. Chen*, C. T. Yue, K. J. Qiao, L. Wang. A Correlation-Guided Layered Prediction Approach for Evolutionary Dynamic Multiobjective Optimization [J]. IEEE Transactions on Evolutionary Computation, 2022, Doi: 10.1109/TEVC.2022.3193287. IF: 16.497, 中科院一区.(paper)(code)

  • K. J. Qiao, K. J. Yu, B. Y. Qu, J. J. Liang*, C. T. Yue, X. X. Ban. Feature Extraction for Recommendation of Constrained Multi-Objective Evolutionary Algorithms [J]. IEEE Transactions on Evolutionary Computation, 2022. Doi: 10.1109/TEVC.2022.3186667. IF: 16.497, 中科院一区 (paper)

  • K. J. Qiao, K. J. Yu, B. Y. Qu, J. J. Liang*, H. Song, C. T. Yue, H. Y. Lin, K. C. Tan. Dynamic Auxiliary Task-Based Evolutionary Multitasking for Constrained Multi-objective Optimization [J]. IEEE Transactions on Evolutionary Computation, 2022. Doi: 10.1109/TEVC.2022.3175065. IF: 16.497, 中科院一区 (paper)(code)(CATF fcuntion code)

  • P. Wang, B. Xue, J. J. Liang*, M. Zhang, Differential Evolution Based Feature Selection: A Niching-based Multi-objective Approach [J]. IEEE Transactions on Evolutionary Computation, 2022. Doi: 10.1109/TEVC.2022.3168052. IF: 16.497, 中科院一区 (paper)

  • J. J. Liang, K. J. Qiao, K. J. Yu*, B. Y. Qu, C. T. Yue, W. F. Guo, L. Wang. Utilizing the Relationship between Unconstrained and Constrained Pareto Fronts for Constrained Multi-Objective Optimization. IEEE Transactions on Cybernetics, 2022, doi: 10.1109/TCYB.2022.3163759. IF: 19.118, 中科院一区. (paper)(code) 

  • K. J. Qiao, J. J. Liang*, B. Y. Qu, K. J. Yu, C. T. Yue, and H. Song. Differential evolution with level-based learning mechanism [J]. Complex System Modeling and Simulation, 2022, 2 (1): 35-58. (paper)(code)

  • Y. Hu , J. Wang, J. J. Liang*, Y. L. Wang, U. Ashraf , C. T. Yue, K. J. Yu. A two-archive model based evolutionary algorithm for multimodal multi-objective optimization problems[J]. Applied Soft Computing, 2022, 119: 108606. IF: 6.725, 中科院二区. (paper)(code)

  • J. J. Liang, X. X. Ban, K. J. Yu*, B. Y. Qu, K. J. Qiao, C. T. Yue, K. C, K. C. Tan. A Survey on Evolutionary Constrained Multi-objective Optimization [J]. IEEE Transactions on Evolutionary Computation, 2022,  27(2): 201-221. IF: 16.497, 中科院一区. (paper)

  • K. J. Qiao, K. J. Yu, B. Y. Qu, J. J. Liang*, H. Song, C. T. Yue. An Evolutionary Multitasking Optimization Framework for Constrained Multi-objective Optimization Problems [J]. IEEE Transactions on Evolutionary Computation, 2022, 26(2): 263-277. IF: 11.554, 中科院一区(paper)(code)

  • M. Y. Yu, J. J. Liang, Z. Wu, Z. L. Yang. A twofold infill criterion-driven heterogeneous ensemble surrogate-assisted evolutionary algorithm for computationally expensive problems [J]. Knowledge-Based Systems, 2022, 236: 107747. IF: 8.139, 中科院一区. (paper)

  • K. J. Qiao, J. J. Liang, K. J. Yu, M. H. Yuan, B. Y. Qu, C. T. Yue. Self-adaptive resources allocation-based differential evolution for constrained evolutionary optimization[J]. Knowledge-Based Systems, 2022, 235: 107653. IF: 8.139, 中科院一区.(paper) (code)


‖ 2021

  • P. Wang, B. Xue, J. J. Liang*, M. J. Zhang. Multiobjective Differential Evolution for Feature Selection in Classification [J]. IEEE Transactions on Cybernetics, 2021. IF: 11.448, 中科院一区.  (paper)

  • J. J. Liang, G. L. Chen, B. Y. Qu, C. T. Yue, K. J. Yu, K. J. Qiao. Niche-based cooperative co-evolutionary ensemble neural network for classification [J]. Applied Soft Computing, 2021, 113: 107951. IF: 6.725, 中科院二区. (paper)

  • J. J. Liang, X. X. Ban, K. J. Yu*, B. Y. Qu, K. J. Qiao. Differential Evolution with Rankings-Based Fitness Function for Constrained Optimization Problems[J]. Applied Soft Computing, 2021, 113: 108016. IF: 6.725, 中科院二区. (paper)(code)

  • C. T. Yue, P. N. Suganthan*, J. J. Liang*, B. Y. Qu, K. J. Yu, Y. S. Zhu, and Y. Li. Differential Evolution Using Improved Crowding Distance for Multimodal Multiobjective Optimization[J]. Swarm and Evolutionary Computation, 2021, 62: 100849. IF: 7.717, 中科院一区. (paper)(code)

  • W. F. Guo, X. T. Yu, Q. Q. Shi, J. J. Liang *, S. W. Zhang*, and T. Zeng*. Performance Assessment of Sample-Specific Network Control Methods for Bulk and Single Cell Biological Data Analysis[J]. PLoS Computational Biology, 2021, 17(5): 1008962. IF: 4.475, 中科院一区.(paper)

  • W. F. Guo, S. W. Zhang*, Y. H. Feng, J. J. Liang, T Zeng*, and L. N. Chen*. Network Controllability-Based Algorithm to Target Personalized Driver Genes for Discovering Combinatorial Drugs of Individual Patients[J]. Nucleic Acids Research, 2021, 49(7): 37. IF: 16.971, 中科院一区.(paper)

  • M. Y. Yu, J. J. Liang, K. Zhao, and Z. Wu*. An Arbf Surrogate-Assisted Neighborhood Field Optimizer for Expensive Problems[J]. Swarm and Evolutionary Computation, 2021, 13(28): 100972. IF: 7.717, 中科院一区.(paper)

  • Y. Hu, B. Y. Qu, J. Wang, J. J. Liang *, Y. L. Wang, K. J. Yu, Y. X. Li, and K. J. Qiao. Short-Term Load Forecasting Using Multimodal Evolutionary Algorithm and Random Vector Functional Link Network-Based Ensemble Learning[J]. Applied Energy, 2021, 285: 116415. IF: 9.746, 中科院一区.(paper)

  • K. J. Yu, J. J. Liang*, B. Y. Qu, Y. Luo, and C. T. Yue. Dynamic Selection Preference-Assisted Constrained Multiobjective Differential Evolution[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021, 52(5): 2954-2965. IF: 13.451, 中科院一区.(paper)

  • K. J. Yu, J. J. Liang*, B. Y. Qu, and C. T. Yue. Purpose-Directed Two-phase Multiobjective Differential Evolution for Constrained Multiobjective Optimization[J]. Swarm and Evolutionary Computation, 2021, 60: 100799. IF: 7.717, 中科院一区.(paper)

  • J. J. Liang*, Y. P. Wei, B. Y. Qu, C. T. Yue, and H. Song. Ensemble Learning Based on Fitness Euclidean-Distance Ratio Differential Evolution for Classification[J]. Natural Computing, 2021, 20: 77-87. IF: 1.69, 中科院四区.(paper)

  • X. J. Jia, J. J. Liang, K. Zhao, Z. L. Yang, and M. Y. Yu*. Multi-Parameters Optimization for Electromagnetic Acoustic Transducers Using Surrogate-Assisted Particle Swarm Optimizer[J]. Mechanical Systems and Signal Processing, 2021, 152: 107337. IF: 6.823, 中科院一区.(paper)


‖ 2020

  • J. J. Liang, K. J. Qiao, C. T. Yue, K. J. Yu, B. Y. Qu*, R. H. Xu, Z. M. Li, and Y. Hu. A Clustering-Based Differential Evolution Algorithm for Solving Multimodal Multi-Objective Optimization Problems[J]. Swarm and Evolutionary Computation, 2020, 60: 100788. IF: 7.717, 中科院一区.(paper)(code)

  • J. J. Liang, G. L. Chen, B. Y. Qu, K. J. Yu*, C. T. Yue, K. J. Qiao, and H. Qian*. Cooperative Co-Evolutionary Comprehensive Learning Particle Swarm Optimizer for Formulation Design of Explosive Simulant[J]. Memetic Computing, 2020, 12 (4): 331-341. IF: 5.9, 中科院三区.(paper)

  • J. J. Liang, K. J. Qiao, K. J. Yu*, S. L. Ge, B. Y. Qu, R. H. Xu, and K. Li. Parameters Estimation of Solar Photovoltaic Models via A Self-Adaptive Ensemble-Base Differential Evolution[J]. Solar Energy, 2020, 207: 336-346. IF: 5.742, 中科院二区.(paper)(code)

  • J. J. Liang, K. J. Qiao, M. H. Yuan, K. J. Yu*, B. Y. Qu, S. L. Ge, Y. X. Li, and G. L. Chen. Evolutionary Multi-Task Optimization for Parameters Extraction of Photovoltaic Models[J]. Energy Conversion and Management, 2020, 207: 112509. IF: 9.709, 中科院一区.(paper)

  • Z. P. Cheng, Z. W. Li*, J. J. Liang, J. K. Si, L. H. Dong, and J. F. Gao. Distributed Coordination Control Strategy for Multiple Residential Solar PV Systems in Distribution Networks[J]. International Journal of Electrical Power & Energy Systems, 2020, 117: 105660. IF: 4.63, 中科院二区.(paper)

  • C. T. Yue, J. J. Liang*, B. Y. Qu, Y. H, Han, Y. S, Zhu, and O. D. Crisalle. A Novel Multiobjective Optimization Algorithm for Sparse Signal Reconstruction[J]. Signal Processing, 2020, 167: 107292-107304. IF: 4.662,中科院二区.(paper)

  • J. J. Liang, S. L. Ge, B. Y. Qu, K. J. Yu*, F. G. Liu, H. T. Yang, P. P. Wei, and Z. M. Li. Classified Perturbation Mutation Based Particle Swarm Optimization Algorithm for Parameters Extraction of Photovoltaic Models[J]. Energy Conversion and Management, 2020, 203: 112138. IF: 9.709, 中科院一区.(paper)【ESI高被引】

  • B. Y. Qu, C. Li, J. J. Liang, L. Yan*, K. J. Yu, and Y. S. Zhu. A Self-Organized Speciation Based Multiobjective Particle Swarm Optimizer for Multimodal Multiobjective Problems[J]. Applied Soft Computing, 2020, 86: 105886. IF: 6.725, 中科院二区.(paper)

  • M. Y. Yu, X. Li, and J. J. Liang*. A Dynamic Surrogate-Assisted Evolutionary Algorithm Framework for Expensive Structural Optimization[J]. Structural and Multidisciplinary Optimization, 2020, 61(2): 711-729. IF: 4.542, 中科院二区.(paper)

  • B. Qu, C. Li, J. Liang, L. Yan, K. Yu, Y. Zhu. A self-organized speciation based multi-objective particle swarm optimizer for multimodal multi-objective problems[J]. Applied Soft Computing, 2020, 86: 105886. IF: 6.725, 中科院二区.(paper)(code)


‖ 2019

  • Z. P. Cheng, Z. W. Li*, J. J. Liang, J. F. Gao, J. K. Si, and S. H. Li. Distributed Economic Power Dispatch and Bus Voltage Control for Droop-Controlled DC Microgrids[J]. Energies, 2019, 12(7):1400. IF: 2.702, 中科院三区.(paper)

  • Z. W. Li, Z. P. Cheng*, J. J. Liang, J. K. Si, L. H. Dong, and S. H. Li. Distributed Event-Triggered Secondary Control for Economic Dispatch and Frequency Restoration Control of Droop-Controlled AC Microgrids[J]. IEEE Transactions on Sustainable Energy. 2019, 11(3): 1938-1950. IF: 7.44, 中科院一区.(paper)

  • Y. L. Wang, B. Y. Qu, J. J. Liang*, Y. P. Wei, C. T. Yue, Y. Hu, and H. Song. Two-Stage Decomposition Method Based on Cooperation Coevolution for Feature Selection on High-Dimensional Classification[J]. IEEE Access, 2019,7: 163191-163201. IF: 3.745, 中科院二区.(paper)

  • J. J. Liang, H. T. Yang, J. J. Gao, C. T. Yue, S. L. Ge, and B. Y. Qu*. MOPSO-Based CNN for Keyword Selection on Google Ads[J]. IEEE Access, 2019, 7: 125387-125400. IF: 3.745, 中科院二区.(paper)

  • W. Z. Zhang, G. Q. Li, W. W. Zhang, J. J. Liang, and G. G. Yen*. A Cluster Based PSO with Leader Updating Mechanism and Ring-Topology for Multimodal Multiobjective Optimization[J]. Swarm and Evolutionary Computation, 2019, 50: 100569. IF: 6.912,中科院二区.(paper)

  • J. J. Liang, P. Wang, L. Guo, B. Y. Qu*, C. T. Yue, K. J. Yu, and Y. C. Wang. Multiobjective Flow Shop Scheduling with Limited Buffers Using Hybrid Self-Adaptive Differential Evolution[J]. Memetic Computing, 2019, 11(4): 407-422. IF: 3.860, 中科院三区.(paper)

  • C. T. Yue, B. Y. Qu, K. J. Yu, J. J. Liang*, and X. D. Li. A Novel Scalable Test Problem Suite for Multimodal Multiobjective Optimization[J]. Swarm and Evolutionary Computation, 2019, 48: 62-71. IF: 6.912, 中科院二区.(paper)(code)

  • Q. K. Pan, L. Gao*, L. Wang, J. J. Liang, and X. Y. Li. Effective Heuristics and Metaheuristics to Minimize Total Flowtime for The Distributed Permutation Flowshop Problem[J]. Expert Systems with Applications, 2019, 124: 309-324. IF: 5.452, 中科院二区.(paper)【ESI高被引】

  • K. J. Yu, B. Y. Qu, C. T. Yue, S. L. Ge, X. Chen, and J. J. Liang*. A Performance-Guided JAYA Algorithm for Parameters Identification of Photovoltaic Cell and Module[J]. Applied Energy, 2019, 237: 241-257. IF: 8.848, 中科院一区.(paper)(code)【ESI高被引】

  • Y. Hu, J. Wang, J. J. Liang*, K. J. Yu, H. Song, Q. Q. Guo, C. T. Yue, and Y. L. Wang. A Self-Organizing Multimodal Multiobjective Pigeon-Inspired Optimization Algorithm[J]. Science China-Information Sciences, 2019, 62(7): 70206. IF: 3.304, 中科院二区.(paper)(code)

  • Z. W. Li*, Z. P. Cheng, Y. L. Xu, Y. F. Wang, J. J. Liang, and J. F. Gao. Hierarchical Control of Parallel Voltage Source Inverters in AC Microgrids[C]. The Journal of Engineering, 2019(16): 1149-1152. (paper)

  • J. J. Liang, W. W. Xu, C. T. Yue, K. J. Yu, H. Song, O. C. Crisalle, and B. Y. Qu*. Multimodal Multiobjective Optimization with Differential Evolution[J]. Swarm and Evolutionary Computation, 2019, 44: 1028-1059. IF: 6.912, 中科院二区.(paper)(code)

  • B. Y. Qu, J. J. Liang*, Y. S. Zhu and P. N. Suganthan. Solving Dynamic Economic Emission Dispatch Problem Considering Wind Power by Multi-Objective Differential Evolution with Ensemble of Selection Method[J]. Natural Computing, 2019, 18(4): 695-703. IF: 0.860, 中科院四区.(paper)

  • Y. S. Zhu, B. H. Qiao, Y. Dong, B. Y. Qu, D. Y. Wu. Multiobjective dynamic economic emission dispatch using evolutionary algorithm based on decomposition[J]. IEEJ Transactions on Electrical & Electronic Engineering, 2019, 14(9).1323-1333. IF: 0.668, 中科院四区. (paper)(code)

  • Z. Li, L. Shi, C. Yue, Z. Shang, B. Qu. Differential evolution based on reinforcement learning with fitness ranking for solving multimodal multiobjective problems[J]. Swarm and Evolutionary Computation, 2019. IF: 6.912, 中科院二区. (paper)


‖ 2018

  • K. J. Yu, J. J. Liang*, B. Y. Qu, Z. P. Cheng, and H. S. Wang. Multiple Learning Backtracking Search Algorithm for Estimating Parameters of Photovoltaic Models[J]. Applied Energy, 2018, 226: 408-422. IF: 8.426, 中科院一区.(paper)(code)【ESI高被引】

  • C. T. Yue, B. Y. Qu, and J. J. Liang. A Multiobjective Particle Swarm Optimizer Using Ring Topology for Solving Multimodal Multiobjective Problems[J]. IEEE Transactions on Evolutionary Computation, 2018, 22(5): 805-817. IF: 8.508, 中科院一区.(paper)(code)【ESI高被引】

  • K. J. Yu, L. While, M. Reynolds, X. Wang, J. J. Liang, L. Zhao*, and Z. L. Wang*. Multiobjective Optimization of Ethylene Cracking Furnace System Using Self-Adaptive Multiobjective Teaching-Learning-Based Optimization[J]. Energy, 2018, 148: 469-481. IF: 5.537, 中科院二区.(paper)

  • B. Y. Qu, Y. S. Zhu, Y. C. Jiao, M. Y. Wu, P. N. Suganthan, and J. J. Liang*. A Survey on Multiobjective Evolutionary Algorithms for the Solution of the Environmental/Economic Dispatch Problems[J]. Swarm and Evolutionary Computation, 2018, 38: 1-11. IF: 6.330, 中科院二区.(paper)

  • G. Li*, J. Wang*, J. J. Liang, and C. T. Yue. Application of Sliding Nest Window Control Chart in Data Stream Anomaly Detection[J]. Symmetry, 2018, 10(4): 113. IF: 2.143, 中科院三区.(paper)

  • G. Li, J. Wang*, J. J. Liang*, and C. T. Yue. The Application of a Double CUSUM Algorithm in Industrial Data Stream Anomaly Detection[J]. Symmetry, 2018, 10(7): 264. IF: 2.143, 中科院三区.(paper)


‖ 2017

  • B. Y. Qu, Q. Zhou, J. M. Xiao, J. J. Liang*, and P. N. Suganthan. Large Scale Portfolio Optimization Using Multiobjective Evolutionary Algorithms and Pre-Selection Methods[J]. Mathematical Problems in Engineering, 2017, 2017: 1-14. IF: 1.145, 中科院四区.(paper)

  • K. J. Yu, J. J. Liang*, B. Y. Qu, X. Chen, and H. S. Wang. Parameters Identification of Photovoltaic Models Using an Improved JAYA Optimization Algorithm[J]. Energy Conversion and Management, 2017, 150: 742-753. IF: 6.377, 中科院一区.(paper)(code)【ESI高被引】

  • C. T. Yue, J. J. Liang*, B. F. Lang, and B. Y. Qu. Two-hidden-layer Extreme Learning Machine Based Wrist Vein Recognition System[J]. Big Data & Information Analytics, 2017, 2(1): 59. IF: 1.352, 中科院四区.(paper)

  • Lynn, N., & Suganthan, P. N. (2017). Ensemble particle swarm optimizer. Applied Soft Computing, 55, 533-548. IF: 3.907, 中科院二区.(paper)(code)


‖ 2016

  • B. Y. Qu, J. J. Liang*, Y. S. Zhu, Z. Y. Wang and P. N. Suganthan. Economic Emission Dispatch Problems with Stochastic Wind Power Using Summation Based Multi-Objective Evolutionary Algorithm[J]. Information Sciences, 2016, 351: 48-66. IF: 4.832，中科院二区.(paper)

  • B. Y. Qu, B. F. Lang, J. J. Liang*, A. K. Qin and O. D. Crisalle. Two-hidden-layer Extreme Learning Machine for Regression and Classification[J]. Neurocomputing, 2016, 175: 826-834. IF: 3.317, 中科院二区.(paper)

  • B. Y. Qu, J. J. Liang*, Z. Y. Wang, Q. Chen, P. N. Suganthan. Novel Benchmark Functions for Continuous Multimodal Optimization with Comparative Results[J]. Swarm and Evolutionary Computation, 2016, 26: 23-34. IF: 3.893, 中科院二区.(paper)

  • X. Chu*, B. Niu, J. J. Liang, Q. Lu. An Orthogonal-design Hybrid Particle Swarm Optimizer with Application to Capacitated Facility Location Problem[J]. International Journal of Bio-Inspired Computation, 2016, 8(5): 268-285. IF: 1.935, 中科院二区.(paper)


‖ 2015

  • L. L. Wu, Q. H. Zhou, T. J. Chen, J. J. Liang, X. Wu. Application of Particle Swarm Optimization Method to Incoherent Scatter Radar Measurement of Ionosphere Parameters[J]. Journal of Geophysical Research: Space Physics, 2015, 120(9): 8096-8110. IF: 2.733, 中科院三区.(paper)

  • Lynn, N., & Suganthan, P. N. (2015). Heterogeneous comprehensive learning particle swarm optimization with enhanced exploration and exploitation. Swarm and Evolutionary Computation, 24, 11-24. (paper)(code)


‖ 2014

  • J. J. Liang, H. Song, B. Y. Qu*. Comparison of Three Different Curves Used in Path Planning Problems Based on Particle Swarm Optimizer[J]. Mathematical Problems in Engineering, 2014, 2014. IF:0.762, 中科院四区.(paper)

  • J. J. Liang, B. Y. Qu, X. B. Mao, B. Niu, D.Y. Wang. Differential Evolution Based on Fitness Euclidean-distance Ratio for Multimodal Optimization[J]. Neurocomputing, 2014, 137: 252-260. IF:2.083, 中科院三区.(paper)


‖ 2013

  • Y. Y. Han, J. J. Liang, Q. K. Pan, J. Q. Li. Effective Hybrid Discrete Artificial Bee Colony Algorithms for The Total Flowtime Minimization in The Blocking Flowshop Problem[J]. The International Journal of Advanced Manufacturing Technology, 2013, 67(1-4): 397-414. IF: 1.779, 中科院三区.(paper) 

  • B. Y. Qu, P. N. Suganthan, S. Das. A distance-based locally informed particle swarm model for multimodal optimization[J]. IEEE Transactions on Evolutionary Computation, 2013, 17(3): 387-402. IF: 5.545, 中科院一区.(paper)(code)


‖ 2012

  • B. Y. Qu, P. N. Suganthan, and J. J. Liang. Differential Evolution with Neighborhood Mutation for Multimodal Optimization[J]. IEEE Transactions on Evolutionary Computation, 2012, 16(5): 601-614. IF: 4.810, 中科院一区.(paper)(code)

  • B. Y. Qu, J. J. Liang, P. N. Suganthan. Niching Particle Swarm Optimization with Local Search for Multi-modal Optimization[J]. Information Sciences, 2012, 197: 131-143. IF: 3.643, 中科院二区.(paper)(code)

  • K. Z. Gao, Q. K. Pan, J. Q. Li, Y. T. Wang, J. J. Liang. A Hybrid Harmony Search Algorithm for The No-wait Flow-shop Scheduling Problems[J]. Asia-Pacific Journal of Operational Research, 2012, 29(02): 1250012. IF: 0.303, 中科院四区.(paper)


‖ 2011

  • J. J. Liang, Q. K. Pan, T. J. Chen, L. Wang. Solving The Blocking Flow Shop Scheduling Problem by A Dynamic Multi-Swarm Particle Swarm Optimizer[J]. The International Journal of Advanced Manufacturing Technology, 2011, 55(5-8): 755-762. IF: 1.103, 中科院四区.(paper)

  • Q. K. Pan, P. N. Suganthan, J. J. Liang, M. F. Tasgetiren. A Local-best Harmony Search Algorithm with Dynamic Sub-harmony Memoriesfor Lot-streaming Flow Shop Scheduling Problem[J]. Expert Systems with Applications, 2011, 38(4): 3252-3259. IF: 2.203, 中科院二区.(paper)

  • Zhao, S. Z., & Suganthan, P. N. (2011). Two-lbests based multi-objective particle swarm optimizer. Engineering Optimization, 43(1), 1-17. IF: 0.936, 中科院三区. (paper)(code)

  • B. Y. Qu*, P. N. Suganthan*, "Constrained Multi-Objective Optimization Algorithm with Ensemble of Constraint Handling Methods", Engineering Optimization, vol. 43,no.4, pp.403-416, Mar 2011. IF: 0.936, 中科院三区. (paper)(code)


‖ 2010

  • Q. K. Pan, P. N. Suganthan, M. F. Tasgetiren, J. J. Liang. A Self-Adaptive Global Best Harmony Search Algorithm for Continuous Optimization Problems[J]. Applied Mathematics and Computation, 2010, 216(3): 830-848. IF: 1.536, 中科院二区.(paper)

  • Q. K. Pan, P. N. Suganthan, J. J. Liang, M. F. Tasgetiren. A Local-best Harmony Search Algorithm with Dynamic Subpopulations[J]. Engineering Optimization, 2010, 42(2): 101-117. IF: 0.966, 中科院四区.(paper)

  • B. Y. Qu*, P. N. Suganthan, “Multi-Objective Evolutionary Algorithms based on the Summation of Normalized Objectives and Diversified Selection”, Information Sciences, vol. 180, no. 17, pp. 3170-3181, Sept. 2010. IF: 2.836, 中科院一区.(paper)(code)


‖ 2007

  • V. L. Huang, P. N. Suganthan, J. J. Liang, C. C. Chan. Improving the performance of a FBG sensor network using a novel dynamic multi-swarm particle swarm optimizer[J]. Proceedings of SPIE - The International Society for Optical Engineering, 2007, 1(8):373-378.(paper)


‖ 2006

  • J. J. Liang, C. C. Chan, P. N. Suganthan, V. L. Huang. Wavelength Detection in FBG Sensor Network Using Tree Search DMS-PSO[J]. IEEE Photonics Technology Letters, 2006, 18(12): 1305-1307. IF: 2.468, 中科院三区. (paper)

  • J. J. Liang, P. N. Suganthan, A. K. Qin, S. Baska. Comprehensive Learning Particle Swarm Optimizer for Global Optimization of Multimodal Functions[J]. IEEE Transactions on Evolutionary Computation, 2006, 10(3): 281-295. IF: 11.554, 中科院一区. (paper)(code)

  • V. L. Huang, P. N. Suganthan, and J. J. Liang*. Comprehensive Learning Particle Swarm Optimizer for Solving Multiobjective Optimization Problems[J]. International Journal of Intelligent Systems, 2006, 21(2): 209-226. IF: 0.429, 中科院四区.(paper)

  • J. J. Liang*, S. Baskar, P. N. Suganthan, and A. K. Qin. Performance Evaluation of Multiagent Genetic Algorithm[J]. Natural Computing, 2006, 5(1): 83-96(14). IF: 1.495, 中科院四区.(paper)


‖ 2005

  • S. Baskar, A. Alphones, P. N. Suganthan, and J. J. Liang*. Design of Yagi-Uda Antennas Using Comprehensive Learning Particle Swarm Optimisation[J]. IEEE Proceedings on Microwaves, Antenna and Propagation, 2005, 152(5): 340-346. IF: 0.494, 中科院四区.(paper)


‖ 中文论文

  • 朱政宇, 侯庚旺, 黄崇文, 孙钢灿, 郝万明, 梁静*. 基于并行CNN的RIS辅助D2D保密通信系统资源分配算法. 通信学报,2022,43(03):172-179. (paper)

  • 李亚欣，梁静*，岳彩通，李珂. 基于适应度地形分析地进化计算研究综述. 陕西师范大学学报（自然科学版），2021，49(5): 42-56.(paper)

  • 王艳丽，梁静*，薛冰，岳彩通. 基于进化计算的特征选择方法研究概述. 郑州大学学报（工学版），2020, 41(1): 49-57.(paper)

  • 梁静，葛士磊，瞿博阳，于坤杰*. 求解电力系统经济调度问题的改进粒子群优化算法. 控制与决策，2020，8，1813-1822.(paper)

  • 梁静，郭倩倩，岳彩通，瞿博阳*. 自组织多目标粒子群优化算法. 计算机应用研究，2019，36(8): 1-8.(paper)

  • 许伟伟，梁静*，岳彩通，瞿博阳. 多模态多目标差分进化算法求解非线性方程组. 计算机应用研究，2019，36(5): 1-7.(paper)(code)

  • 梁静，刘睿，于坤杰，瞿博阳*. 求解大规模问题协同进化动态粒子群优化算法. 软件学报，2018，29(9): 2595-2605.(paper)

  • 梁静*，刘睿，瞿博阳，岳彩通. 进化算法在大规模优化问题中的应用综述. 郑州大学学报（工学版），2018，39(3): 15-21.(paper)

  • 李广，王杰*，梁静，朱晓东，岳彩通. 石油钻井工程预警技术发展概述. 郑州大学学报（工学版），2017，38(6): 70-73.(paper)

  • 李广, 王杰*, 梁静, 岳彩通, 范业活, 宋殿光, 吕泽鹏. 基于随机森林的钻井工程预警研究. 石油天然气学报，2017, 39(4): 193-198.(paper)

  • 梁静，宋慧，王龙，瞿博阳. 多目标优化在中央空调节能优化系统中的应用. 计算机仿真，2015, 32(6): 302-307.(paper)

  • 梁静，瞿博阳，宋慧，刘巍. 电业超短期负荷预测仿真研究. 计算机仿真，2015, 32(7): 96-101.(paper)

  • 瞿博阳，梁静*，王忠勇，郭丽. 模式识别双语教学中学生科研素质的提升. 计算机教育，2015，12: 1-3.(paper)

  • 梁静,宋慧,瞿博阳. 基于改进粒子群算法的路径优化问题研究. 郑州大学学报（工学版）, 2014, 35(1): 34-38.(paper)

  • 梁静，宋慧，瞿博阳. 多目标优化在路径优化中的应用. 计算机仿真，2014，31(4): 364-368.(paper)

  • 梁静，周钦亚，瞿博阳，宋慧. 基于混合策略的差分进化算法. 郑州大学学报（工学版），2013, 34(5): 59-62.(paper)

  • 毛晓波, 梁静, 黄俊杰. 研究生“智能仪器与仪表”课程教改探索. 电气电子教学学报, 2012, 34(3): 50-51.(paper)

  • 韩红燕, 潘全科, 梁静. 改进的和声搜索算法在函数优化中的应用. 计算机工程, 2010, 36(13):245-247.(paper)




友情链接

郑州大学计算智能实验室