Improvement of the distance between intuitionistic fuzzy sets and its applications

Article type: Research Article

Authors: Xu, Changlin^{; *}

Affiliations: School of Mathematics and Information Science, Beifang University of Nationalities, Yinchuan, China

Correspondence: [*] Corresponding author. Changlin Xu, School of Mathematics and Information Science, Beifang University of Nationalities, Yinchuan 750021, China. Email: xu_changlin@nun.edu.cn.

Abstract: In this paper novel measuring distances (Minkowski distances) between intuitionistic fuzzy sets (IFSs) are given by a detailed analysis of the distance measures for IFSs proposed in the past. In the new method, the membership degree and non-membership degree are introduced into the distances between IFSs, while the assignments of the hesitancy degree to membership degree and non-membership degree are also considered, which is consistent with human cognition. The advantage of the novel distance measures are compared in depth by artificial intuitionistic fuzzy sets presented in literature. Finally, we demonstrate the efficiency of the proposed distance measures based on the pattern recognition problems and medical diagnosis.

Keywords: Intuitionistic fuzzy sets, distance measure, similarity measure, pattern recognition, medical diagnosis

DOI: 10.3233/JIFS-17276

Journal: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 3, pp. 1563-1575, 2017