Data Clustering Using Particle Swarm Optimization

Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 309)

Abstract

K-Means clustering algorithm attracts increasing focus in recent years. A pending problem of K-Means clustering algorithm is that the performance is affected by the original cluster centers. In this paper the K-Means algorithm is improved by particle swarm optimization and the initial cluster centers are generated by particle swarm optimization..The experiments and comparisons with the classical K-Means algorithm indicate that the improved k-mean clustering algorithm has obvious advantages on execution time.

Keywords

particle swarm optimization K-Means clustering 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Mingru Zhao
    • 1
    • 2
  • Hengliang Tang
    • 1
    • 2
  • Jian Guo
    • 2
  • Yuan Sun
    • 2
  1. 1.Beijing Municipal Key Laboratory of Multimedia and Intelligent Software Technology , College of Computer Science and TechnologyBeijing University of TechnologyBeijingChina
  2. 2.Beijing Key Laboratory of Intelligent Logistics SystemBeijing Wuzi UniversityBeijingChina

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