Aiming at the problem that the sensitivity of initial value and noise lead to the decline of fuzzy C-means clustering,fuzzy C-means clustering method of neighborhood granule is proposed by introducing the theory of granular computation and using the neighborhood granulation technique.In the sample,the neighborhood granule is constructed by using the neighborhood granulation technique on single feature,and the neighborhood granular vector is formed by using granulation on multi-features.A variety of granule distance formulas are defined to measure the distance between granules.According to the granule distance measurement,a granular fuzzy C-means clustering method is proposed,and a granular fuzzy C-means clustering algorithm is designed.Multiple data sets are used to perform experiments,and the fuzzy C-means clustering algorithm is compared with the classical clustering algorithm.The results verify the feasibility and effectiveness of the proposed neighborhood granular fuzzy C-means clustering method.
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