系统工程与电子技术

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模糊C均值聚类区间型模糊化参数模型

肖满生1,2, 肖哲1, 文志强2, 于惠钧1   

  1. 1. 湖南工业大学科技学院, 湖南 株洲 412008; 
    2. 湖南工业大学计算机与通信学院, 湖南 株洲 412008
  • 出版日期:2015-03-18 发布日期:2010-01-03

Interval type fuzzifier parameter model in fuzzy C means clustering

XIAO Man-sheng1,2, XIAO Zhe1, WEN Zhi-qiang2, YU Hui-jun1   

  1. 1. College of Science and Technology, Hunan University of Technology, Zhuzhou 412008, China;
     2. College of Computer and Communication, Hunan University of Technology, Zhuzhou 412008, China
  • Online:2015-03-18 Published:2010-01-03

摘要:

针对经典模糊C均值聚类算法中模糊加权指数对聚类的影响及其取值范围不确定性问题,提出了一种区间型模糊加权指数的设计模型。分析该模型设计的理论依据及对聚类结果的影响,推导出包括模糊隶属度划分矩阵、模糊聚类中心等基于该模型的模糊化参数表示方法。理论分析和实验证明,区间型模糊化参数模型的设计在基于模糊划分的数据处理中取得了很好的效果。

Abstract:

Aiming at the problem about the effect of the fuzzy weighted index in classical fuzzy C means clustering algorithm and the value of uncertainty, the model of interval type fuzzy weighted index is proposed. Theoretical basis of the model and its effect on the clustering results are analyzed. Based on this model, the fuzzifier parameter such as fuzzy membership partition matrix, fuzzy clustering center representation is derived. The theoretical analysis and experimental results show that the interval type fuzzifier parameter model designing has achieved good effect based on data processing of fuzzy partition.