关键词: 聚类分析, 粒子群算法, K-均值算法, 遗传算法

Abstract: This paper proposes a clustering algorithm which is based on improved Particle Swarm Optimization（PSO）.Both the K-means，which has strong capacity of local searching，and the cross，mutation operation，which are based on the genetic algorithm，are combined in the PSO algorithm.It not only improves the PSO’s local searching capacity，accelerates the convergence rate，and effectively prevents the premature convergence，for it adds cross and mutation operations.Experiments show that this clustering algorithm has a better convergence.

Key words: cluster analysis, particle swarm optimization algorithm, K-means, genetic algorithm