[1] 杨智,陈志堂,范正平,李晓东. 基于改进粒子群优化算法的PID控制器整定[J]. 控制理论与应用,2010, 27(10):1345-1352. Yang Z, Chen Z T, Fan Z P, Li X D. Tuning of PID controller based on improved particleswarm-optimization[J]. Control Theory & Application, 2010, 27(10):1345-1352. (in Chinese)
[2] 余胜威,曹中清. 基于人群搜索算法的PID控制器参数优化[J]. 计算机仿真,2014, 31(9):347-350. Yu S W, Cao Z Q. Optimization parameters of PID controller parameters based on seeker optimization algorithm[J]. Computer Simulation, 2014, 31(9):347-350. (in Chinese)
[3] Echevarría L C, Santiago O L, Fajardo J A H, Neto A J S, Sánchez D J. A variant of the particle swarm optimization for the improvement of fault diagnosis in industrial systems via faults estimation[J]. Engineering Applications of Artifcial Intelligence, 2014, 28:36-51.
[4] Kennedy J, Eberhart R. Particle swarm optimization[C]//IEEE International Conference on Neural Networks, Perth, Australia, 1995:1942-1948.
[5] 孟丽,韩璞,任燕燕,王东风. 基于多目标粒子群的PID控制器设计[J]. 计算机仿真,2013, 30(7):388-391. Meng L, Han P, Ren Y Y, Wang D F. Design of PID Controller based on multi-objective particle swarm optimization algorithm[J]. Computer Simulation, 2013, 30(7):388-391. (in Chinese)
[6] 陶新民,刘福荣,刘玉,童智靖. 一种多尺度协同变异的粒子群优化算法[J]. 软件学报,2012, 23(7):1805-1815. Tao X M, Liu F R, Liu Y, Tong Z J. Multi-scale cooperative mutation particle swarm optimization algorithm[J]. Journal of Software, 2012, 23(7):1805-1815. (in Chinese)
[7] Ni Q J, Zhang Z Z, Wang Z Z, Xing H C. Dynamic probabilistic particle swarm optimization based on varying multi-cluster structure[J]. Journal of Software, 2009, 20(2):339-349.
[8] 王建林,吴佳欢,张超然,赵利强,于涛. 基于自适应进化学习的多目标粒子群优化算法[J]. 控制与决策,2014, 29(2):1-6. Wang J L, Wu J H, Zhang C R, Zhao L Q, Yu T. Constrained multi-objective particle swarm optimization algorithm based on self-adaptive evolutionary learning[J]. Control and Decision, 2014, 29(2):1-6. (in Chinese)
[9] Kennedy J. The particle swarm:social adaptation of knowledge[C]//IEEE International Conference on Evolutionary Computation, 1997:303-308.
[10] 黄泽霞,俞攸红,黄德才. 惯性权自适应调整的量子粒子群优化算法[J]. 上海交通大学学报,2012, 46(2):228-232. Huang Z X, Yu Y H, Huang D C. Quantum-behaved particle swarm algorithm with selfadapting adjustment of inertia weight[J]. Journal of Shanghai Jiaotong University, 2012, 46(2):228-232. (in Chinese)
[11] Clerc M, Kennedy J. The particle swarm-explosion, stability and convergence in a multidimensional complex space[J]. IEEE Trans. Evol. Comput. 2002, 6:58-73.
[12] Kennedy J, Eberhart R. Particle swarm optimization[C]//IEEE International Conference on Neural Networks, Perth, Australia, 1995:1942-1948.
[13] Poli R. An analysis of publications on particle swarm optimization applications[D]. Department of Computer Science, University of Essex, 2007.
[14] 米根锁,梁利,杨润霞. 灰色变异粒子群算法载客车流量预测中的应用[J]. 计算机工程与科学,2015, 31(1):361-363. Mi G S, Liang L, Yang R X. Application of the grey mutation particle swarm algorithm in urban public transport passenger volume prediction[J]. Computer Engineering and Science, 2015, 31(1):361-363. (in Chinese) |