%0 Journal Article
%A XIONG Yongjun
%A LIU Weiguo
%A OU Pengjie
%T New optimized fuzzy C-means clustering algorithm
%D 2015
%R
%J Computer Engineering and Applications
%P 124-128
%V 51
%N 11
%X In the light of the randomness of the initial clustering center selection and the limitations of distance vector formula application with the traditional Fuzzy C-Means clustering algorithm （FCM）, the optimized fuzzy C-means clustering algorithm （FCMBMD） is proposed. The algorithm is to determine the initial cluster center by computing the density of sample point, so it avoids the instability of clustering result generated randomly by initial cluster centers. In addition, it also meets the requirements of different units of measurement data using the similarity of Mahalanobis distance calculation sample set. The experimental result shows that FCMBMD algorithm has better effect in clustering center, convergence speed, iterations, accuracy, and so on.
%U http://cea.ceaj.org/EN/abstract/article_33289.shtml