Clustering model based on weighted intuitionistic fuzzy sets
Shibin Zhang · Journal of Computer Applications · 2012
Concerning the limitations of the existing clustering methods based on intuitionistic fuzzy sets,a clustering model called Weighted Intuitionistic Fuzzy Set Model(WIFSCM) was proposed based on weighted intuitionistic fuzzy sets.In this model,the concepts of equivalent sample and weighted intuitionistic fuzzy set were put forward in special feature space,and based on which the objective function of intuitionistic fuzzy clustering algorithm was proposed.Iterative algorithms of clustering center and matrix of membership degree were inferred from the objective function.The density function based on weighted intuitionistic fuzzy sets was defined,and initial clustering center was gotten to reduce iterative times.The experiment of gray image segmentation shows that WIFSCM is effective,and it is faster than IFCM algorithm nearly a hundred times.