关键词: K-调和均值, 混沌粒子群, 聚类

Abstract: In view of the advantages and disadvantages of K-harmonic means and chaos particle swarm optimization clustering algorithm，a chaos particle swarm optimization clustering algorithm merged with K-harmonic means is provided.Particle swarm is firstly divided into sub-groups，resulting in an iterative process for each particle based on its extreme value and location of the individual sub-populations in the global extremum to update their position.Secondly，the introduction of variable-scale chaotic mutation，inhibit the premature convergence and improve the calculation accuracy.The new algorithm can avoid the algorithm into a local optimum，guarantee the convergence speed while enhancing the capacity of global search algorithms，improve the clustering efficiency.

Key words: K-harmonic means, chaotic particle swarm optimization, cluster