重庆理工大学学报：自然科学2012，Vol.26Issue(12)：79-83,5.
一种基于浓度的粒子群优化算法
An Improved PSO Algorithm Based Density
摘要
Abstract
In order to solve premature convergence to local minimum problem of PSO,a new method is introduced to improve PSO performance on global optimization problem.Through introducing the density from immune algorithm,the particle can update effectively and improve the global search capability for finding the global optimum.A comparison is made with the standard PSO by five benchmark functions.The experimental results illustrate that the proposed algorithm has evident superiorities in search precision and convergence speed.关键词
粒子群算法/浓度/免疫算法/收敛Key words
PSO/density/immune algorithm/convergence分类
信息技术与安全科学引用本文复制引用
李庆芳,孙合明..一种基于浓度的粒子群优化算法[J].重庆理工大学学报：自然科学,2012,26(12):79-83,5.
