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A Particle Swarm Clustering Algorithm with Fuzzy Weighted Step Sizes

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Intelligent Data Engineering and Automated Learning – IDEAL 2015 (IDEAL 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9375))

Abstract

This paper proposes a modification in the Fuzzy Particle Swarm Clustering (FPSC) algorithm such that membership degrees are used to weight the step size in the direction of the local and global best particles, and in its movement in the direction of the input data at every iteration. This results in the so-called Membership Weighted Fuzzy Particle Swarm Clustering (MWFPSC). The modified algorithm was applied to six benchmark datasets from the literature and its results compared to that of the standard FPSC and FCM algorithms. By introducing these modifications it could be observed a gain in accuracy, representativeness of the clusters found and the final Xie-Beni index, at the expense of a slight increase in the practical computational time of the algorithm.

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Notes

  1. 1.

    http://archive.ics.uci.edu/ml/datasets.html.

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Acknowledgment

The authors thank FAPESP, CNPq, and CAPES for their financial support.

Author information

Authors and Affiliations

  1. Federal University of ABC, Santo André, Brazil

    Alexandre Szabo

  2. Federal University of Technology of Paraná, Curitiba, Brazil

    Myriam Regattieri Delgado

  3. Natural Computing Laboratory, Mackenzie University, São Paulo, Brazil

    Alexandre Szabo & Leandro Nunes de Castro

Authors
  1. Alexandre Szabo
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  2. Myriam Regattieri Delgado
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  3. Leandro Nunes de Castro
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Corresponding author

Correspondence to Alexandre Szabo .

Editor information

Editors and Affiliations

  1. Wroclaw University of Technology, Wroclaw, Poland

    Konrad Jackowski

  2. Department of Systems, Wroclaw University of Technology, Wroclaw, Poland

    Robert Burduk

  3. Wroclaw Univ of Tech, Wroclaw, Poland

    Krzysztof Walkowiak

  4. Wroclaw University of Technology, Faculty of Electronics, Wroclaw, Poland

    Michal Wozniak

  5. School of Electrical & Electronic E, University of Manchester, Manchester, United Kingdom

    Hujun Yin

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© 2015 Springer International Publishing Switzerland

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Szabo, A., Delgado, M.R., de Castro, L.N. (2015). A Particle Swarm Clustering Algorithm with Fuzzy Weighted Step Sizes. In: Jackowski, K., Burduk, R., Walkowiak, K., Wozniak, M., Yin, H. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2015. IDEAL 2015. Lecture Notes in Computer Science(), vol 9375. Springer, Cham. https://doi.org/10.1007/978-3-319-24834-9_11

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  • DOI: https://doi.org/10.1007/978-3-319-24834-9_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24833-2

  • Online ISBN: 978-3-319-24834-9

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