Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (16): 130-131.DOI: 10.3778/j.issn.1002-8331.2010.16.038

• 数据库、信号与信息处理 • Previous Articles     Next Articles

Clustering algorithm based on Particle Swarm Optimization with mutation

LIU Qiong,LUO Ke   

  1. Department of Computer & Communication Engineering,Changsha University of Science and Technology,Changsha 410114,China
  • Received:2008-11-12 Revised:2009-02-09 Online:2010-06-01 Published:2010-06-01
  • Contact: LIU Qiong


刘 琼,罗 可   

  1. 长沙理工大学 计算机与通信工程学院,长沙 410114
  • 通讯作者: 刘 琼

Abstract: Aiming at premature convergence and convergence speed of basic particle swarm optimization algorithm,the clustering algorithm based on particle swarm optimization algorithm with mutation is proposed.A mutation operator is used in the algorithm for some particles to escape from the local optimal solution.The algorithm is evaluated on Iris plants database.Results show that the algorithm not only avoids local optima,but also increases the convergence speed.

Key words: Particle Swarm Optimization algorithm, clustering analysis, K-means algorithm

摘要: 针对基本粒子群算法的早熟收敛和收敛较慢的问题,提出了一种带变异操作的粒子群聚类算法。算法中对出现早熟收敛的种群采取变异操作,使其能够跳出局部最优解。对Iris植物样本数据的测试结果表明:该算法具有很好的全局收敛性和较快的收敛速度。

关键词: 粒子群算法, 聚类分析, K均值算法

CLC Number: