%0 Journal Article
%T Self-adaptive Particle Swarm OPtimization Algorithm Based on Tentative Adjusting Step Factor<br>基于试探的变步长自适应粒子群算法
%A ZHENG Chun-ying
%A ZHENG Quan-di
%A WANG Xiao-dan
%A WANG Yu-bing
%A <br>郑春颖
%A 郑全弟
%A 王晓丹
%A 王玉冰
%J 计算机科学
%D 2009
%I 
%X Aiming at premature defect and poor result of Particle Swarm Optimization algorithm, a new Self-adaptive inertia factor was designed according to diversity in the population and generation number based on analysing inertia factor's effect of algorithm. And through ploughing around adjusting step factors,the Particle's ability in local searching was enhanced. Three typical function tests were given. Comparing with APSO, the result indicates the effectiveness of this improvement.
%K Particle swarm optimization algorithm
%K Inertia factor
%K Generation number<br>粒子群算法
%K 惯性因子
%K 进化代数
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=D16007825050986318FEF85205233452&yid=DE12191FBD62783C&vid=933658645952ED9F&iid=708DD6B15D2464E8&sid=23104246A5FCFCEF&eid=64963996248CBF47&journal_id=1002-137X&journal_name=计算机科学&referenced_num=1&reference_num=8