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Article type: Research Article
Authors: Vicente, Eloy | Jiménez-Martín, Antonio | Mateos, Alfonso
Affiliations: Decision Analysis and Statistics Group, Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, Campus de Montegancedo S/N, Boadilla del Monte, Madrid, Spain
Note: [] Corresponding author. Eloy Vicente, Decision Analysis and Statistics Group, Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, Campus de Montegancedo S/N, Boadilla del Monte, 28660 Madrid, Spain. E-mails: e.vicentecestero@upm.es (Eloy Vicente), ajimenez@fi.upm.es (Antonio Jim'enez-Martín), amateos@fi.upm.es (Alfonso Mateos).
Abstract: Different functions for quantifying the degree of similarity between two fuzzy numbers have been proposed in the literature on the basis of various descriptive parameters, such as the geometric distance, the distance between the centers of gravity, the perimeters or the shared area between the fuzzy numbers. However, these similarity functions are not equally applicable across all situations. Consequently, comparative analyses have been performed on the basis of different sets of fuzzy number pairs. In this paper we thoroughly review the similarity functions proposed in the literature, identify their properties and possible drawbacks and compare them on the basis of an extended set of fuzzy numbers.
Keywords: Similarity functions, fuzzy numbers
DOI: 10.3233/IFS-141364
Journal: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 2, pp. 821-833, 2015
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