The theory of fuzzy sets, proposed by Zadeh, has gained
successful applications in various fields. Measures of similarity between fuzzy sets have gained attention from researchers for their wide applications in real world. Similarity measures are very useful in some areas, such as pattern
recognition, machine learning, decision making and market prediction etc. Many
measures of similarity between fuzzy sets have been proposed.
Atanassov presented intuitionistic fuzzy sets which are very
effective to deal with vagueness. Gau and Buehere researched vague sets.
Bustince and Burillo pointed out that the notion of vague sets is same as that of interval-valued intuitionistic fuzzy sets. Chen and Tan proposed two
similarity measures for measuring the degree of similarity between vague sets.
De et al. defined some operations on intuitionistic fuzzy sets. Szmidt and
Kacprzyk introduced the Hamming distance between intuitionistic fuzzy sets and
proposed a similarity measure between intuitionistic fuzzy sets based on the
distance.
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