Individual Cognitive Parameter Setting Based on Black Stork Foraging Process

摘要：

Cognitive learning factor is an important parameter in particle swarm optimization algorithm(PSO). Although many selection strategies have been proposed, there is still much work need to do. Inspired by the black stork foraging process, this paper designs a new cognitive selection strategy, in which the whole swarm is divided into adult and infant particle, and each kind particle has its special choice. Simulation results show this new strategy is superior to other two previous modifications.

关键词： particle swarm optimization cognitive learning factor black stork foraging process

作者: Zhihua Cui

作者单位: Complex System and Computational Intelligence Laboratory, Taiyuan University of Science and Technology, Shanxi, P.R.China, 030024

会议类型: 国际会议

会议名称: 2009 Ninth International Conference on Hybrid Intelligent Systems(第九届混合智能系统国际会议 HIS 2009)

会议地点: 沈阳

会议语种:英文

页码: 1-5

在线出版日期: 2009-08-12（万方平台首次上网日期，不代表论文的发表时间）