A New Method for Measuring Similarity between Intuitionistic Fuzzy Sets Based on Normal Distribution Functions

  • Authors:

  • Zehua Lv;Chuanbo Chen;Wenhai Li

  • Affiliations:

  • Huazhong University of Science and Technology;Huazhong University of Science and Technology;Huazhong University of Science and Technology

  • Venue:
  • FSKD '07 Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 02
  • Year:
  • 2007

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Abstract

This paper puts forward a new kind of similarity measure between Intuitionistic Fuzzy Sets (IFSs) based on normal distribution functions. At first, we propose a method to express an intuitionistic fuzzy set by a series of normal distribution functions. Then, we use these normal distribution functions to calculate the degree of similarity between IFSs. The properties of the proposed similarity measure are proved and several numerical examples are taken to validate it. Compared with the existing methods, the proposed similarity measure is more reasonable and more suitable for any special situation. Moreover, by comparing the proposed similarity measure with the existing measures, our method shows that it is much more reliable than the existing measures to linguistic variables. Though having a little difficulty for calculation, the similarity measure presents a brand- new method to deal with fuzzy information.