Intuitionistic fuzzy C-means clustering algorithms

作     者：Zeshui Xu Junjie Wu 

作者机构：School of Economics and ManagementSoutheast UniversityNanjing 210096P.R.China Institute of SciencesPLA University of Sciences and TechnologyNanjing 210007P.R.China Department of Information SystemsSchool of Economics and ManagementBeihang UniversityBeijing 100191P.R.China 

出 版 物：《Journal of Systems Engineering and Electronics》 (系统工程与电子技术(英文版))

年 卷 期：2010年第21卷第4期

页      面：580-590页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 0808[工学-电气工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 081104[工学-模式识别与智能系统] 08[工学] 0802[工学-机械工程] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the National Natural Science Foundation of China for Distinguished Young Scholars(70625005) 

主　　题：intuitionistic fuzzy set(IFS) intuitionistic fuzzy Cmeans algorithm clustering interval-valued intuitionistic fuzzy set(IVIFS). 

摘      要：Intuitionistic fuzzy sets(IFSs) are useful means to describe and deal with vague and uncertain *** intuitionistic fuzzy C-means algorithm to cluster IFSs is *** each stage of the intuitionistic fuzzy C-means method the seeds are modified,and for each IFS a membership degree to each of the clusters is *** the end of the algorithm,all the given IFSs are clustered according to the estimated membership ***,the algorithm is extended for clustering interval-valued intuitionistic fuzzy sets(IVIFSs).Finally,the developed algorithms are illustrated through conducting experiments on both the real-world and simulated data sets.