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On ranking fuzzy numbers using valuations
Author(s) -
Yager Ronald R.,
Filev Dimitar
Publication year - 1999
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/(sici)1098-111x(199912)14:12<1249::aid-int6>3.0.co;2-c
Subject(s) - ranking (information retrieval) , computer science , fuzzy logic , artificial intelligence , fuzzy number , mathematics , data mining , machine learning , fuzzy set
The importance as well as the difficulty of the problem of ranking fuzzy numbers is pointed out. Here we consider approaches to the ranking of fuzzy numbers based upon the idea of associating with a fuzzy number a scalar value, its valuation, and using this valuation to compare and order fuzzy numbers. Specifically we focus on expected value type valuations which are based upon the transformation of a fuzzy subset into an associated probability distribution. We develop a number of families of parameterized valuation functions. ©1999 John Wiley & Sons, Inc.