中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
An enhanced Kernel Fuzzy C-Means Algorithm based on bio-inspired computing methods

文献类型:会议论文

作者Liu Y(刘洋); Hu KY(胡琨元); Zhu YL(朱云龙); Chen HN(陈瀚宁)
出版日期2014
会议名称International Conference on Electronics, Information Technology and Intellectualization, EITI 2014
会议日期August 16-17, 2014
会议地点Shenzhen, China
关键词data clustering bio-inspired computing optimization algorithm Kernel Fuzzy C-Means Algorithm Artificial Bee Colony
页码115-118
中文摘要In data analysis and data mining technique fields, one of the most widely used methods is clustering. Recently, one of the bio-inspired computing optimization algorithms called the Artificial Bee Colony (ABC) algorithm has been introduced, which has many characteristics, such as simple, robust, stochastic global optimization. In this paper, an enhancedKernel Fuzzy C-MeansAlgorithm (KFCM) based on theABC algorithm for data clustering is proposed. Compared with other popular bio-inspired computing optimization algorithms in data clustering, the results proved that the number of iterations is fewer, the convergence speed is faster and there is also a large improvement in the quality of clustering.
收录类别EI
产权排序1
会议录Electronics, Information Technology and Intellectualization - International Conference on Electronics, Information Technology and Intellectualization, EITI 2014
会议录出版者Taylor & Francis Group
会议录出版地London
语种英语
ISBN号978-1-138-02741-1
源URL[http://ir.sia.cn/handle/173321/20081]  
专题沈阳自动化研究所_信息服务与智能控制技术研究室
推荐引用方式
GB/T 7714
Liu Y,Hu KY,Zhu YL,et al. An enhanced Kernel Fuzzy C-Means Algorithm based on bio-inspired computing methods[C]. 见:International Conference on Electronics, Information Technology and Intellectualization, EITI 2014. Shenzhen, China. August 16-17, 2014.

入库方式: OAI收割

来源:沈阳自动化研究所

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