Journal of South China University of Technology (Natural Science Edition) ›› 2014, Vol. 42 ›› Issue (9): 65-69.doi: 10.3969/j.issn.1000-565X.2014.09.012

• Electronics, Communication & Automation Technology • Previous Articles     Next Articles

GK Clustering Model Based on Optimal Initial Clustering Center of AFS

Wang Li- na1 Chen Xiao- hong2   

  1. 1.School of Geography∥ Center for Wisdom Land and Environmental Study,South China Normal University,Guangzhou 510630,Guangdong,China; 2.Center of Water Resources and Environment Research∥ Key Laboratory of Water Cycle and Water Security in Southern China of Guangdong Higher Education Institutes,Sun Yat- Sen University,Guangzhou 510275,Guangdong,China
  • Received:2014-04-23 Revised:2014-06-05 Online:2014-09-25 Published:2014-08-01
  • Contact: 陈晓宏(1963-)，男，教授，主要从事水文、水资源与环境研究． E-mail:eescxh@mail.sysu.edu.cn
  • About author:汪丽娜(1981-)，女，副教授，主要从事水资源的异变性研究．E-mail:linawang2004@163．com
  • Supported by:

    国家自然科学基金资助项目(51210013，51479216);国家科技支撑计划项目(2012BAC21B0103);教育部高等学校博士学科点专项科研基金新教师类资助课题(20114407120006);广东省自然科学基金博士启动项目(S2011040005992);广东高校优秀青年创新人才培养计划(育苗工程)项目(LYM11049);水利部公益项目(201201094，201301002-02);广东省水利科技创新项目(2011-11)

PDF

804

Abstract:

Gustafson- Kessel (GK) clustering algorithm can be used to search for hyper ellipsoid,plane and lineardata effectively,but it is still sensitive to initial clustering center and easy to fall into a local optimum.In order tosolve this problem,this paper presents an improved GK clustering algorithm,which adopts the artificial fish- swarm(AFS) algorithm to initialize clustering centers according to the similarity between clustering and searching food offish school.Then,this algorithm is employed to perform a simulation based on artificial data and IRIS data.Theresults show that the improved algorithm can find the clustering structure of datasets effectively,and it possesses abetter classification performance than GK clustering algorithm.

Key words: cluster analysis, GK clustering algorithm, optimization, initial cluster center