A new similarity measure of fuzzy numbers

Article type: Research Article

Authors: Chou, Chien-Chang

Affiliations: Department of Shipping Technology, National Kaohsiung Marine University and Chou's Science Research Center, Chi-Chin, Kaohsiung, Taiwan

Note: [] Corresponding author. Chien-Chang Chou, Department of Shipping Technology, National Kaohsiung Marine University and Chou's Science Research Center 482, Chung-Chou 3rd Road, Chi-Chin 805, Kaohsiung, Taiwan. E-mail: chiench1@ms58.hinet.net

Abstract: A new method for measuring the degree of similarity between fuzzy numbers is proposed in this paper. The advantage of the proposed method is to take account of the membership functions of fuzzy numbers while measuring the degree of similarity of fuzzy numbers. Finally, six sets of fuzzy numbers are used to compare the proposed method with the existing methods for similarity measure of fuzzy numbers. The results show that the proposed method for similarity measure seems to be more reasonable.

Keywords: Fuzzy sets theory, fuzzy number, similarity measure, membership function

DOI: 10.3233/IFS-120737

Journal: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 1, pp. 287-294, 2014