A Cosine Similarity Measure Based on the Choquet Integral for Intuitionistic Fuzzy Sets and Its Applications to Pattern Recognition

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OLGUN M., Türkarslan E., ÜNVER M., Ye J.

INFORMATICA, vol.32, no.4, pp.849-864, 2021 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 32 Issue: 4
  • Publication Date: 2021
  • Doi Number: 10.15388/21-infor460
  • Journal Name: INFORMATICA
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, INSPEC, zbMATH
  • Page Numbers: pp.849-864
  • Keywords: Choquet integral, cosine similarity measure, intuitionistic fuzzy set, pattern recognition, VAGUE SETS
  • TED University Affiliated: Yes

Abstract

There exist various types of similarity measures for intuitionistic fuzzy sets in the literature. However, in many studies the interactions among the elements are ignored in the construction of the similarity measure. This paper presents a cosine similarity measure for intuitionistic fuzzy sets by using a Choquet integral model in which the interactions between elements are considered. The proposed similarity measure is applied to some pattern recognition problems and the results are compared with some existing results to demonstrate the effectiveness of this new similarity measure.