%0 Journal Article
%T The Strategy of Parameters-selection for PSO Based on Differential Evolutions<br>基于微分演化的PSO参数选择策略
%A DOU Quan-Sheng
%A ZHOU Chun-Guang
%A ZHANG Zhong-Bo
%A LIU Xiao-Hua
%A <br>窦全胜
%A 周春光
%A 张忠波
%A 刘小华
%J 计算机科学
%D 2007
%I 
%X The Particle Swarm Optimization (PSO)method was originally designed by Kennedy and Eberhart in 1995 and has been applied successfully in various optimization problems. The PSO idea is inspired by natural concepts such as fish schooling, bird flocking and human social relations. The track of each particle is controlled by some parameters and highly sensitive to different parameters setting. So how to choice the optimum parameters is key for PSO. The strategy of parameter-selection is proposed, which dose not depend on expert experience, the performance of PSO is be regarded as a function decided by parameters of PSO in this strategy, So, the problem of parameters-selection is be transform to optimization problem, at the same time, differential evolution (DE)is be used for solving this optimization problem.
%K Particle swarm optimization
%K Differential evolution<br>粒子群方法
%K 微分演化
%K PSO
%K 参数选择
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=EFB38901E80C3770FDF6EAA06EDD0188&yid=A732AF04DDA03BB3&vid=339D79302DF62549&iid=E158A972A605785F&sid=CA5852BD1A173B3A&eid=D6354F61445E9456&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=18