On ordered weighted averaging aggregation operators in multicriteria decisionmaking
IEEE Transactions on Systems, Man and Cybernetics
Fuzzy Sets and Systems
Measures of entropy and fuzziness related to aggregation operators
Information Sciences—Intelligent Systems: An International Journal
Analytic properties of maximum entropy OWA operators
Information Sciences—Informatics and Computer Science: An International Journal
Information Processing and Management: an International Journal - Modelling vagueness and subjectivity in information access
International Journal of Intelligent Systems
Computers and Industrial Engineering
Weighted maximum entropy OWA aggregation with applications to decision making under risk
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
OWA operators with maximal Rényi entropy
Fuzzy Sets and Systems
THE FUZZY GENERALIZED OWA OPERATOR AND ITS APPLICATION IN STRATEGIC DECISION MAKING
Cybernetics and Systems
OWA aggregation over a continuous interval argument with applications to decision making
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A linguistic modeling of consensus in group decision making basedon OWA operators
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Including importances in OWA aggregations using fuzzy systems modeling
IEEE Transactions on Fuzzy Systems
OWA operators in data modeling and reidentification
IEEE Transactions on Fuzzy Systems
Neural fuzzy logic programming
IEEE Transactions on Neural Networks
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In this paper, based upon the M-Entropy measures, two new models for obtaining the ordered weighted averaging (OWA) operators are propoosed. In these models, it is assumed, according to available information, that the OWA weights are in a decreasing or increasing order. Some properties of the models are analyzed, and the method of Lagrange multipliers is used to provide a direct way to find these weights. The models are solved with a specific level of orness comparing the results with some other related models. The results demonstrate the efficiency of the M-Entropy models in generating the OWA operator weights. © 2012 Wiley Periodicals, Inc.