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Data Clustering Based on Particle Swarm Optimization with Neighborhood Search and Cauchy Mutation

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Neural Information Processing (ICONIP 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8835))

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Abstract

K-means is one of the most popular clustering algorithm, it has been successfully applied in solving many practical clustering problems, however there exist some drawbacks such as local optimal convergence and sensitivity to initial points. In this paper, a new approach based on enhanced particle swarm optimization (PSO) is presented (denoted CMPNS), in which PSO is enhanced by new neighborhood search strategy and Cauchy mutation operation. Experimental results on fourteen used artificial and real-world datasets show that the proposed method outperforms than that of some other data clustering algorithms in terms of accuracy and convergence speed.

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Author information

Authors and Affiliations

  1. State Key Laboratory of Software Engineering, Computer School, Wuhan University, Wuhan, 430072, China

    Dang Cong Tran & Zhijian Wu

  2. Vietnam Academy of Science and Technology, Hanoi, Vietnam

    Dang Cong Tran

Authors
  1. Dang Cong Tran
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  2. Zhijian Wu
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Editor information

Editors and Affiliations

  1. Department of Artificial Intelligence, Faculty of Computer Science and Information Technology Building, University of Malaya, 50603, Kuala Lumpur, Malaysia

    Chu Kiong Loo

  2. Department of Electronics and Communication Engineering, College of Engineering, Universiti Tenaga Nasional, Jalan IKRAM-UNITEN, 43009, Kajang, Selangor, Malaysia

    Keem Siah Yap

  3. School of Engineering and Information Technology, Murdoch University, South St., 6150, Murdoch, Western Australia, Australia

    Kok Wai Wong

  4. Department of Electrical and Electronics Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, 120-749, Seoul, South Korea

    Andrew Teoh

  5. Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, Ren’ai Road 111, SIP 215123, Suzhou, Jiangsu Province, China

    Kaizhu Huang

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© 2014 Springer International Publishing Switzerland

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Tran, D.C., Wu, Z. (2014). Data Clustering Based on Particle Swarm Optimization with Neighborhood Search and Cauchy Mutation. In: Loo, C.K., Yap, K.S., Wong, K.W., Teoh, A., Huang, K. (eds) Neural Information Processing. ICONIP 2014. Lecture Notes in Computer Science, vol 8835. Springer, Cham. https://doi.org/10.1007/978-3-319-12640-1_19

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  • DOI: https://doi.org/10.1007/978-3-319-12640-1_19

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12639-5

  • Online ISBN: 978-3-319-12640-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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