Journal of Software:2002.13(10):1905-1914

关于切换回归的集成模糊聚类算法 GFC
An Integrated Fuzzy Clustering Algorithm GFC for Switching Regressions
WANG Shi-tong,JIANG Hai-feng,LU Hong-jun
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Received:March 29, 2001    Revised:August 31, 2001
> 中文摘要: 已经有多个方法可用于解决切换回归问题.根据所提出的基于Newton引力定理的引力聚类算法GC,结合模糊聚类算法,进一步提出了新的集成模糊聚类算法 GFC.理论分析表明GFC 能收敛到局部最小.实验结果表明GFC在解决切换回归问题时,比标准模糊聚类算法更有效,特别在收敛速度方面.
中文关键词: 切换回归  模糊聚类  引力聚类
Abstract:In order to solve switching regression problems, many approaches have been investigated. In this paper, anintegrated fuzzy clustering algorithm GFC that combines gravity-based clustering algorithm GC with fuzzy clustering is presented. GC, as a new hard clustering algorithm presented here, is based on the well-known Newton's Gravity Law. The theoretic analysis shows that GFC can conve rge to a local minimum of the object function. Experimental results show that GFC for switching regression problems has better performance than standard fuzzy clustering algorithms, especially in terms of convergence speed.
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王士同,江海峰,陆宏钧.关于切换回归的集成模糊聚类算法 GFC.软件学报,2002,13(10):1905-1914

WANG Shi-tong,JIANG Hai-feng,LU Hong-jun.An Integrated Fuzzy Clustering Algorithm GFC for Switching Regressions.Journal of Software,2002,13(10):1905-1914