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PSO优化算法的参数研究
引用本文:赵娜,贾世魁,王健,孙志礼.PSO优化算法的参数研究[J].机械与电子,2013(11):3-6.
作者姓名:赵娜  贾世魁  王健  孙志礼
作者单位:[1]东北大学机械学院,辽宁沈阳110819 [2]沈阳化工大学机械工程学院,辽宁沈阳110142
基金项目:国家自然科学基金资助项目(51205052)
摘    要:分析了惯性权重与学习因子对算法性能的影响,相应提出了几种调整策略并对其优缺点进行比较,之后基于前人的基础数据,借助Matlab软件进行编程,对6种组合调整策略进行优化试验,并与前人试验的最优解进行比较,最终通过试验数据,找出了一种较为可行的优化调整策略.

关 键 词:PSO算法  惯性权重  学习因子  最优解

Survey on the Parameters of Particle Swarm Optimization
Affiliation:ZHAO Na ,JIA Shi - kui ,WANG Jian ,SUN Zhi - li ( 1. School of Mechanical Engineering, Northeastern University, Shenyang 110819, China ; 2. School of Mechanical Engineering,Shenyang University of Chemical Technology,Shenyang 110142, China)
Abstract:This article analyzes the ettects of in- ertia weight and learning factors on the perform- ance of the algorithm, proposes several correspond- ing strategies and their advantages and compares the advantages and disadvantages between them, then uses matlab to program for the six combina- tions of adjustment strategies to test and compares the results with previous trials to identify a more feasible optimal strategy.
Keywords:particle swarm optimization(PSO)  inertia weight  learning factor  optimal solution
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