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An Optimized Clustering Algorithm Using Improved Gene Expression Programming

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Computational Intelligence and Intelligent Systems (ISICA 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 575))

Abstract

How to find the better initial center points plays an important role in many clustering applications. In our paper, we propose the novel chromosome representation according to extended traditional gene expression programming used in GEP-ADF. It is aimed at improving the performance of GEP to obtain center points more accurately. Experimental results show that our new algorithm has good performance in clustering and the three real world datasets compared with the other two algorithms.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China with the Grant No. 61573157, the Fund of Natural Science Foundation of Guangdong Province of China with the Grant No. 2014A030313454.

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Authors and Affiliations

  1. College of Mathematics and Informatics, South China Agricultural University, Guangzhou, 510642, China

    Shuling Yang, Kangshun Li, Wei Li & Weiguang Chen

  2. School of Information Engineering, Jiangxi University of Science and Technology, Ganzhou, 341000, China

    Wei Li

Authors
  1. Shuling Yang
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  2. Kangshun Li
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  3. Wei Li
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  4. Weiguang Chen
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Corresponding author

Correspondence to Kangshun Li .

Editor information

Editors and Affiliations

  1. College of Mathematics and Informatics, The South China Agricultural University, Guangzhou, China

    Kangshun Li

  2. School of Computer Science, Guangzhou University, Guangzhou, China

    Jin Li

  3. School of Computer Science and Engineeri, The University of Aizu, Aizu-Wakamatsu, Fukushima, Japan

    Yong Liu

  4. Dept. of Informatics, University of Salerno, Fisciano, Italy

    Aniello Castiglione

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Yang, S., Li, K., Li, W., Chen, W. (2016). An Optimized Clustering Algorithm Using Improved Gene Expression Programming. In: Li, K., Li, J., Liu, Y., Castiglione, A. (eds) Computational Intelligence and Intelligent Systems. ISICA 2015. Communications in Computer and Information Science, vol 575. Springer, Singapore. https://doi.org/10.1007/978-981-10-0356-1_15

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  • DOI: https://doi.org/10.1007/978-981-10-0356-1_15

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-0355-4

  • Online ISBN: 978-981-10-0356-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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