梁靜

自2009年於鄭州大學電氣工程學院任教。

研究方向

演化計算的研究及應用。

主要貢獻

主持國家自然科學基金優秀青年科學基金項目一項、面上項目兩項、青年項目一項、中國博士后特別資助項目一項。

主要論著

C.T.Yue,B.Y.Qu,K.J.Yu,J.J.Liang*and X.D.Li,“Anovel scalable test problem suite for multimodal multiobjective optimization,”Swarm Evolutionary and Computation.vol.48,pp.62-71,2019.

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,” Signal Processing, vol. 167:107292,2020.

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”, Applied Energy, vol. 237, no. 2019, pp. 241-257.

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 multi-objective pigeon-inspired optimization algorithm,” SCIENCE CHINA Information Sciences, 62(5), pp. 070206:1-070206:17, 2019.

C.T.Yue,B.Y.Qu, and J.J.Liang*,“Amultiobjective particle swarm optimizer using ring topology for solving multimodal multiobjective problems”, IEEE Transactions on Evolutionary Computation, vol. 22, no. 5, pp. 805-817, 2018.

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”, Swarm and Evolutionary Computation, vol. 44, pp. 1028-1059, 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”, Applied Energy, vol. 226, no. 2018, pp. 408-422.

B.Y.Qu, Y. S. Zhu, Y. C. Jiao, M. Y. Wu, J. J. Liang*, P. N. Suganthan, “A Survey on multi-objective evolutionary algorithms for the solution of the environmental/economic dispatch problems”, Swarm and Evolutionary Computation, vol. 38, pp. 1-11, 2018.

B.Y.Qu, Q. Zhou, J. M. Xiao, J. J. Liang*, P. N. Suganthan, “Large-scale portfolio optimization using multiobjective evolutionary algorithms and preselection methods.” Mathematical Problems in Engineering, pp. 1-14, 2017.

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, Energy Conversion and Management, vol. 150, pp. 742-753, 2017.

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,” Natural Computing,pp.1-9,2017.

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,” Information Sciences, vol. 351,pp.48-66,2016.

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,” Neurocomputing, vol. 175, pp. 826-834, 2016.

B.Y.Qu, J. J. Liang*, Z. Y. Wang, Q. Chen, P. N. Suganthan, “Novel benchmark functions for continuous multimodal optimization with comparative results,” Swarm and Evolutionary Computation, vol. 26, pp. 23-34, 2016.

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, ” Neurocomputing, vol. 137, pp. 252-260, 2014.

B.Y.Qu, J. J. Liang, P. N. Suganthan, “Niching particle swarm optimization with local search for multi-modal optimization,” Information Sciences, vol. 197, pp. 131-143, 2012 .

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,”International Journal of Advanced Manufacturing Technology, vol. 55 (5-8), pp. 755-762, 2011.

J. J. Liang, C. C. Chan, P. N. Suganthan, V. L. Huang, “Wavelength detection in FBG sensor network using tree search DMS-PSO,”IEEE Photonics Technology Letters, vol. 18(12), pp. 1305 - 1307, 2006.

V.L.Huang,P.N.Suganthan,J.J. Liang, “Comprehensive learning particle swarm optimizer for solving multiobjective optimization problems,” International Journal of Intelligent Systems, vol. 21, no. 2, pp. 209-226, 2006.

J. J. Liang, S. Baskar, P. N. Suganthan, A. K. Qin, “Performance evaluation of multiagent genetic algorithm,” Natural Computing, vol. 5, no. 1, pp. 83-96(14), 2006.

S. Baskar, A. Alphones, P. N. Suganthan, J. J. Liang, “Design of Yagi-Uda antennas using comprehensive learning particle swarm optimisation,”IEE Proceedings on Microwaves, Antenna and Propagation, vol.152, no. 5, pp.340-346,2005.

梁靜，劉睿，於坤傑，瞿博陽，求解大規模問題協同進化動態粒子群優化演演算法。軟體學報,2018(9):2595-2605.

梁靜，郭倩倩，岳彩通，瞿博陽，自組織多目標粒子群優化演演算法，計算機應用研究.2019,36(8):1-8.

梁靜，劉睿，瞿博陽，岳彩通，進化演演算法在大規模優化問題中的應用綜述，鄭州大學學報(工學版),2018,39(3):15-21.

毛曉波，梁靜，黃俊傑，研究生“智能儀器與儀錶”課程教改探索，電氣電子教學學報,2012,03:50-51.

梁靜，周欽亞，瞿博陽，宋慧，基於混合策略的差分進化演演算法，鄭州大學學報(工學版)，2013,34(5):59-62.

梁靜，宋慧，瞿博陽，基於改進粒子群演演算法的路徑優化問題研究，鄭州大學學報(工學版),2014,35(1):34-38.

梁徠靜，宋慧，王龍，瞿博陽，多目標優化在中央空調節能優化系統中的應用，計算機模擬，2015,32(06):302-307.

梁靜，瞿博陽，宋慧，劉巍，電業超短期負荷預測模擬研究，計算機模擬，2015,32(07):96-101.

瞿博陽，梁靜*，王忠勇，郭麗，模式識別雙語教學中學生科研素質的提升，計算機教育2015,(12):1-3.

獲國家發明專利2項、授權軟體著作權5項。科研成果先後獲得教育部自然科學二等獎，河南省科學進步二等獎，河南省教育廳科技成果一等獎等獎項。梁靜教授還獲得國際學術組織和河南省頒發的一系列獎勵和榮譽稱號，如2014 IEEE CIS Outstanding PhD Dissertation Award獲得者、河南省高層次人才、河南省青年五四獎章、河南省青年科技獎、中原.....計劃-中原青年拔尖人才等。