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A Comparative Analysis of Results of Data Clustering with Variants of Particle Swarm Optimization

  • Anima Naik
  • Suresh Chandra Satapathy
  • K. Parvathi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8298)

Abstract

Particle Swarm Optimization (PSO) has been extensively studied, in recent past, for solving various engineering optimization problems. There have been many variants of PSO available in literatures. This paper presents a comparative analysis of few popular variants of PSO on the problem of data clustering. The investigated algorithms are evaluated on many real world datasets and few artificial datasets and clustering results are presented. Further, the results of statistical test on effectiveness of each investigated variants of PSO also demonstrated. The convergence characteristics of each variant are shown for different datasets. This study may be helpful to many researchers in choosing suitable PSO variants for their application.

Keywords

Data Clustering PSO Intra Cluster Distance 

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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Anima Naik
    • 1
  • Suresh Chandra Satapathy
    • 2
  • K. Parvathi
    • 3
  1. 1.MITSRayagadaIndia
  2. 2.ANITSVishakapatnamIndia
  3. 3.CUTMParalakhemundiIndia

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