Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (17): 146-149.DOI: 10.3778/j.issn.1002-8331.2010.17.041

• 数据库、信号与信息处理 • Previous Articles     Next Articles

Weighted spatially fuzzy dynamic clustering algorithm

WANG Guo-wei1,YAN Li1,CHEN Gui-fen1,2   

  1. 1.College of Information and Technology Science,Jilin Agricultural University,Changchun 130118,China
    2.College of Computer Science Technology,Jilin University,Changchun 130062,China
  • Received:2008-11-28 Revised:2009-02-09 Online:2010-06-11 Published:2010-06-11
  • Contact: WANG Guo-wei

一种加权的空间模糊动态聚类算法

王国伟1,闫 丽1,陈桂芬1,2   

  1. 1.吉林农业大学 信息技术学院,长春 130118
    2.吉林大学 计算机科学技术学院,长春 130062
  • 通讯作者: 王国伟

Abstract: Generally the spatial fuzzy clustering algorithm has not differentiated the imbalance between the various attributes and discussed the best classification number.In response to this problem,this paper uses a spatially weighted fuzzy dynamic clustering algorithm.First,the weight of each attribute is accessed using AHP;and then weight is added to the spatial fuzzy dynamic clustering algorithm;finally,the F-distribution of probability statistics is used to determine the best classification number,in order to improve the algorithm’s intelligence.This algorithm is compared with the transitive closure algorithm based on fuzzy equivalent relations.Tests show that the clustering algorithm’s accurate rate is higher than not weighted fuzzy clustering algorithm.

Key words: analytic hierarchy process, fuzzy equivalence relat

摘要: 一般空间模糊聚类算法没有区分各属性之间的不平衡性和讨论分类数何时为最佳,针对这一问题,提出了一种加权空间模糊动态聚类算法。该算法首先利用层次分析法得到各属性的权值;然后将权值与空间模糊动态聚类法相结合;最后利用概率统计中的F-分布来确定最佳分类,以提高空间模糊聚类算法的智能性。将文中算法与基于模糊等价关系的传递闭包方法进行比较,试验表明,该算法聚类准确率要明显高于未加权的模糊聚类算法。

关键词: 层次分析法, 模糊等价关系, 加权空间模糊动态聚类, 最佳分类

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