计算机工程2012，Vol.38Issue(21)：145-147,3.DOI:10.3969/j.issn.1000-3428.2012.21.039
一种改进的小波变异粒子群优化算法
An Improved Particle Swarm Optimization Algorithm with Wavelet Mutation
摘要
Abstract
Particle Swarm Optimization(PSO) algorithm is difficult to deal with the problems of premature and local convergence. In order to solve the problems, an Improved PSO with Wavelet Mutation(IPSOWM) algorithm is proposed. In IPSOWM, mutation operator is undertaken by selecting particles with certain small probability so as to overcome the PSO's drawback of occurring premature convergence and trapping in the local optima. Experimental results on benchmark functions show that the performance of IPSOWM algorithm is obviously superior to that of the other PSO algorithms in references, including convergence precision, convergence rate and stability.关键词
粒子群优化算法/小波变异/小波变异粒子群优化算法/全局最优/鲁棒性Key words
Particle Swarm Optimization(PSO) algorithm/ wavelet mutation/ PSO algorithm with wavelet mutation/ global optimal/ robustness分类
信息技术与安全科学引用本文复制引用
高东慧,董平平,田雨波,周昊天..一种改进的小波变异粒子群优化算法[J].计算机工程,2012,38(21):145-147,3.基金项目
国家部委基金资助项目 （）
江苏省高校自然科学基础研究基金资助项目(07KJB510032) （07KJB510032）
江苏省普通高校研究生科研创新计划基金资助项目(CX10S_007Z) （CX10S_007Z）
