期刊
INFORMATION SCIENCES
卷 178, 期 19, 页码 3775-3790出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2008.06.008
关键词
intuitionistic fuzzy set (IFS); interval-valued intuitionistic fuzzy set (IVIFS); clustering algorithm; association coefficient; lambda-cutting
资金
- National Science Fund for Distinguished Young Scholars of China [70625005]
- National Natural Science Foundation of China [70571087, 70621061]
The intuitionistic fuzzy set (IFS) theory, originated by Atanassov [K. Atanassov, Intuitionistic fuzzy sets, Fuzzy Sets and Systems 20 (1986) 87-96], has been used in a wide range of applications, such as logic programming, medical diagnosis, pattern recognition, and decision making, etc. However, so far there has been little investigation of the clustering techniques of IFSs. In this paper, we define the concepts of association matrix and equivalent association matrix, and introduce some methods for calculating the association coefficients of IFSs. Then, we propose a clustering algorithm for IFSs. The algorithm uses the association coefficients of IFSs to construct an association matrix, and utilizes a procedure to transform it into an equivalent association matrix. The lambda-cutting matrix of the equivalent association matrix is used to cluster the given IFSs. Moreover, we extend the algorithm to cluster interval-valued intuitionistic fuzzy sets (IVIFSs), and finally, demonstrate the effectiveness of our clustering algorithm by experimental results. (c) 2008 Elsevier Inc. All rights reserved.
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