%0 Journal Article
%T Improved Cluster Algorithm Based on K-Means and Particle Swarm Optimization<br>一种改进的粒子群和K均值混合聚类算法
%A Tao Xin-min
%A Xu Jing
%A Yang Li-biao
%A Liu Yu
%A <br>陶新民
%A 徐晶
%A 杨立标
%A 刘玉
%J 电子与信息学报
%D 2010
%I 
%X To deal with the problem of premature convergence of the traditional K-means algorithm, a novel K-means cluster method based on the enhanced Particle Swarm Optimization(PSO) algorithm is presented. In this approach, the stochastic mutation operation is introduced into the PSO evolution, which reinforces the exploitation of global optimum of the PSO algorithm. In order to avoid the premature convergence and speed up the convergence, traditional K-means algorithm is used to explore the local search space more...
%K K-means algorithm
%K Particle Swarm Optimization(PSO) algorithm
%K Stochastic mutation
%K Fitness variance<br>K均值算法
%K 粒子群优化算法
%K 随机变异
%K 适应度方差
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=1319827C0C74AAE8D654BEA21B7F54D3&jid=EFC0377B03BD8D0EF4BBB548AC5F739A&aid=3D4F3C74B73F7329297744DF2DF72643&yid=140ECF96957D60B2&vid=9971A5E270697F23&iid=CA4FD0336C81A37A&sid=08805F9252973BA4&eid=C3BF5C58156BEDF0&journal_id=1009-5896&journal_name=电子与信息学报&referenced_num=0&reference_num=23