Intuitionistic fuzzy MST clustering algorithms

Authors:
Hua Zhao;Zeshui Xu;Shousheng Liu;Zhong Wang
Affiliations:
Institute of Communications Engineering, PLA University of Science and Technology, Nanjing 210007, China and Institute of Sciences, PLA University of Science and Technology, Nanjing 210007, China;Institute of Sciences, PLA University of Science and Technology, Nanjing 210007, China;Institute of Sciences, PLA University of Science and Technology, Nanjing 210007, China;Institute of Sciences, PLA University of Science and Technology, Nanjing 210007, China
Venue:
Computers and Industrial Engineering
Year:
2012

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Abstract

In this paper, we investigate graph theory-based clustering techniques for Atanassov's intuitionistic fuzzy sets (A-IFSs) and interval-valued intuitionistic fuzzy sets (IVIFSs). We start by introducing the concepts of graph, minimum spanning tree (MST), A-IFS, and intuitionistic fuzzy distance, and develop two intuitionistic fuzzy MST clustering algorithms (Algorithms I and II). Then we extend Algorithm II for clustering IVIFSs, and show the effectiveness of our algorithms through some numerical experiments.