Open AccessA New Method for Fuzzy Ranking Based on Possibility and Necessity Measures
Publication year - 2020
Publication title -
international journal of computers and communications
Language(s) - English
Resource type - Journals
ISSN - 2074-1294
DOI - 10.46300/91013.2020.14.4
Subject(s) - rank (graph theory) , closeness , ranking (information retrieval) , fuzzy logic , fuzzy number , data mining , mathematics , computer science , interval (graph theory) , algorithm , fuzzy set , artificial intelligence , combinatorics , mathematical analysis
In this paper, a new method to rank fuzzy numbers is presented. The proposed method based on Possibility and Necessity Measures is called PNM. According to possibility and necessity measures, eight indexes are calculated to extract four rules to rank fuzzy numbers. Also a method to evaluate each rule validation especially when rules’ outcomes yield conflict conclusions is presented. To test PNM performance, some controversial triangular fuzzy numbers are considered. Additionally, four extracted rules are compared with each other and fully analyzed. Furthermore, PNM is compared with other recently proposed methods. Results confirm that PNM is capable to rank a variety of fuzzy numbers and their images with any selected bandwidths, interval and any degree of closeness