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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

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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.

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