关键词: 模糊聚类, 模糊C均值算法, 隶属度矩阵

Abstract: FCM（Fuzzy C-Means） algorithm has several defects，being sensitive to the initial cluster centers，only being applied to the type found in globular clusters.There are several methods used for reducing the algorithm dependence on the initial cluster centers，expressing big cluster or extension of shape used several small clusters.At last，this paper merges adjacent small cluster into a big cluster，using the information provided by partition matrix.Experiment result demonstrates that the improved FCM algorithm can distinguish irregular cluster to a certain extent，decrease the dependence on the initial cluster centers.

Key words: fuzzy clustering, Fuzzy C-Means algorithm（FCM）, partition matrix