[1] 纪震,廖惠莲,吴青华. 粒子群算法及应用[M]. 北京:科学出版社, 2009.
[2] 姜苏英. 基于改进PSO算法的加热系统分数阶控制[J]. 计算机与现代化, 2018(7):43-46.
[3] 张慧. 基于改进GA-PSO的无线传感网络路由算法[J]. 计算机与现代化, 2015(12):31-34.
[4] KENNEDY J, EBERHART R C. Particle swarm optimization [C]// IEEE International Conference on Neural Networks. 1995:1942-1948.
[5] WANG F, ZHANG H, LI K, et al. A hybrid particle swarm optimization algorithm using adaptive learning strategy[J]. Information Sciences, 2018,436-437:162-177.
[6] WANG L, YANG B, ORCHARD J. Particle swarm optimization using dynamic tournament topology[J]. Applied Soft Computing, 2016,48:584-596.
[7] LI K, LIU L, ZHAI J, et al. The improved grey model based on particle swarm optimization algorithm for time series prediction[J]. Engineering Applications of Artificial Intelligence, 2016,55:285-291.
[8] TSAI H. Unified particle swarm delivers high efficiency to particle swarm optimization[J]. Applied Soft Computing, 2017,55:371-383.
[9] 史哲文,白雪石,郭禾. 基于改进小生境粒子群算法的多模函数优化[J]. 计算机应用研究, 2012,29(2):465-468.
[10]张德慧,张德育,刘清云,等. 基于粒子群算法的BP神经网络优化技术[J]. 计算机工程与设计, 2015,36(5):1321-1326.
[11]周欣. 粒子群算法在图像处理中的应用研究[D]. 武汉:湖北工业大学, 2011.
[12]ABIDO A M. Multiobjective particle swarm optimization with nondominated local and global sets[J]. Natural Computing, 2010,9(3):747-766.
[13]SHI Y, EBERHART R. A modified particle swarm optimizer[C]// IEEE International Conference on Evolutionary Computation. 1998:69-73.
[14]EBERHART R, KENNEDY J. A new optimizer using particle swarm theory[C]// Proceedings of the 6th International Symposium on Micro Machine and Human Science. 1995:39-43.
[15]胡旺,李志蜀. 一种更简化而高效的粒子群优化算法[J]. 软件学报, 2007,18(4):861-868.
[16]潘勇,郭晓东. 一种基于遗传算法改进的粒子群优化算法[J]. 计算机应用与软件, 2011,28(9):222-224.
[17]郑申海,胡小兵,郑满满,等. 改进粒子群和模拟退火混合算法及其应用[J]. 计算机技术与发展, 2013,23(7):26-30.
[18]董红斌,李冬锦,张小平. 一种动态调整惯性权重的粒子群优化算法[J]. 计算机科学, 2018,45(2):98-102.
[19]CHEN Y, LI L, PENG H, et al. Particle swarm optimizer with two differential mutation[J]. Applied Soft Computing, 2017,61:314-330.
[20]YE W, FENG W, FAN S. A novel multi-swarm particle swarm optimization with dynamic learning strategy[J]. Applied Soft Computing, 2017,61:832-843.
[21]王帅群,敖日格乐,高尚策,等. 一种新的变异因子选择策略[J]. 计算机科学, 2014,41(9):225-228.
[22]SUN J, FANG W, Palade V, et al. Quantum-behaved particle swarm optimization with Gaussian distributed local attractor point[J]. Applied Mathematics and Computation, 2011,218(7):3763-3775.
[23]WANG C, WANG J, YANG G, et al. Gaussian Particle Swarm Optimization with Differential Evolution Mutation[M]. Springer Berlin Heidelberg, 2011:439-446.
[24]赵新超,刘国莅,刘虎球,等. 基于非均匀变异和多阶段扰动的粒子群优化算法[J]. 计算机学报, 2014,37(9):2058-2070. |