湖北民族学院学报（自然科学版）2016，Vol.34Issue(1)：11-15,5.DOI:10.13501/j.cnki.42-1569/n.2016.03.003
改进惯性权重的简化粒子群优化算法
Simplified Particle Swarm Optimization Algorithm Based on Improved Inertia Weight
摘要
Abstract
For the shortcomings of the traditional particle swarm optimization algorithm,which is easy to fall into local extreme,a new algorithm based on the simplified particle swarm optimization algorithm is proposed.Firstly,it removes the speed term,so it makes the algorithm simple.And then it mproves the dis-placement term.Finally it improves the inertia weight.Six classical functions are used to compare the tradi-tional particle swarm optimization algorithm,the simplified particle swarm optimization algorithm and the improved algorithm proposed in this paper.The experimental results show that the performance of the im-proved particle swarm optimization is better than the other two algorithms.关键词
速度项/惯性权重/经典函数Key words
velocity term/inertia weight/classical functions分类
数理科学引用本文复制引用
高苇,平环,张成刚,姜静清..改进惯性权重的简化粒子群优化算法[J].湖北民族学院学报（自然科学版）,2016,34(1):11-15,5.基金项目
国家自然科学基金项目（61373067，61163034）；内蒙古自然科学基金项目 （）
