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Quantifier guided aggregation using OWA operators
Author(s) -
Yager Ronald R.
Publication year - 1996
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(199601)11:1<49::aid-int3>3.0.co;2-z
Subject(s) - quantifier (linguistics) , extension (predicate logic) , measure (data warehouse) , set (abstract data type) , representation (politics) , quantifier elimination , fuzzy logic , mathematics , fuzzy set , computer science , artificial intelligence , algebra over a field , data mining , discrete mathematics , pure mathematics , programming language , politics , political science , law
We consider multicriteria aggregation problems where, rather than requiring all the criteria be satisfied, we need only satisfy some portion of the criteria. The proportion of the critera required is specified in terms of a linguistic quantifier such as most . We use a fuzzy set representation of these linguistic quantifiers to obtain decision functions in the form of OWA aggregations. A methodology is suggested for including importances associated with the individual criteria. A procedure for determining the measure of “orness” directly from the quantifier is suggested. We introduce an extension of the OWA operators which involves the use of triangular norms. © 1996 John Wiley & Sons, Inc.