摘要
在对粒子群优化(PSO)算法进行深入分析的基础上,建立了自适应邻域更新机制,再对惯性权重更新机制进行自适应化,分别从拓扑邻域结构和惯性权重两个角度对局部版PSO算法进行了改进,提出了一种实用、高效的自适应邻域粒子群优化算法,经7个标准测试函数验证,该算法具有较高效率和精度。
Based on thorough analysis on the existing PSO algorithms, an improved PSO algorithm with adaptive neighborhood was proposed, which included two special improvements： the mechanism of scheduled neighborhood adaptation, and a modified mechanism of scheduled interia weight adaptation. The proposed PSO algorithm is proved to be high-performing and high accurate by 7 standard banchmark functions.
出处
《计算机应用》
CSCD
北大核心
2008年第12期3055-3057,3088,共4页
journal of Computer Applications
基金
国家自然科学基金资助项目(50709008)
关键词
粒子群优化算法
惯性权重
自适应邻域
Particle Swarm Optimization （PSO）
intertia weight
adaptive neighborhood
