Paper:

# New Similarity Measures of Intuitionistic Fuzzy Sets

## Hassan Rezaei and Masao Mukaidono

Department of Computer Science, Meiji University, 1-1-1 Higashi-Mita, Tama-Ku, Kawasaki-shi 214-8571, Japan

In this review of existing similarity measures of intuitionistic fuzzy sets (IFSs), we apply some numerical examples showing that not all existing similarity measures are effective and reasonable in some cases. We propose properties based on intuition and the human thinking process that should be satisfied by all dissimilarity and similarity measures, together with new similarity measures of IFSs that overcome drawbacks of existing measures. In examples, we compare the proposed similarity measures to existing measures and present two propositions on the relationship between similarity and dissimilarity measures of IFSs. We also propose that a suitable combination of similarity measures may be a similarity measure.

*J. Adv. Comput. Intell. Intell. Inform.*, Vol.11, No.2, pp. 202-209, 2007.

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