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 !

‖ 2021

  • 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, 中科院一区. 

  • 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: 108016. IF:6.725, 中科院一区.

  • 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, 2021: 107653. IF:11.448, 中科院一区.

  • 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]. Public Library of Science 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: 1-12. 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)

  • 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.(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)

  • 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)

  • 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, 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. (paper)(code)

  • P. Wang, L. Guo, B. Qu, C. Yue, K. Yu, Y. Wang. Multi-objective flow shop scheduling with limited buffers using hybrid self-adaptive differential evolution[J]. Memetic Computing, 2019: 1-16. (paper)

  • 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. (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)

  • 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)

  • 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)

  • 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. (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. (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. (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. (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. (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

  • 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)