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An Optimized Clustering Algorithm Using Improved Gene Expression Programming

  • Shuling Yang
  • Kangshun LiEmail author
  • Wei Li
  • Weiguang Chen
Conference paper
Part of the Communications in Computer and Information Science book series (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.

Keywords

Center points Novel chromosome representation Gene expression programming GEP-ADF 

Notes

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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Copyright information

© Springer Science+Business Media Singapore 2016

Authors and Affiliations

  • Shuling Yang
    • 1
  • Kangshun Li
    • 1
    Email author
  • Wei Li
    • 1
    • 2
  • Weiguang Chen
    • 1
  1. 1.College of Mathematics and InformaticsSouth China Agricultural UniversityGuangzhouChina
  2. 2.School of Information EngineeringJiangxi University of Science and TechnologyGanzhouChina

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