Induced aggregation operators

By Ronald R. Yager. Fuzzy Sets Syst., 2003

411 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/8bde376df51d3dbcc48d2616e009eeeb8880edee

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In Artificial Intelligence

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Citations in the corpus

The Induced Generalized OWA Operator (2009, methodology): “For example, we could use it for modeling nearest neighbour rule [29], for model building [29] and for the aggregation of complex objects [23].”
Managing the consensus in group decision making in an unbalanced fuzzy linguistic context with incomplete information (2010, methodology): “, pn} the values of the argument variable [12, 52, 53, 54].”
Group Decision-Making Model With Incomplete Fuzzy Preference Relations Based on Additive Consistency (2007, methodology): “This aggregation is carried out by applying a special type of IOWA operator [40]–[42], the AC-IOWA operator (Section V-A2), which is based on the concept of AC [31] (Section III) and that is guided by a linguistic quantifier representing the concept of fuzzy majority (of experts) desired to be imple”
A web based consensus support system for group decision making problems and incomplete preferences (2010, methodology): “To do so, a modified version of the Additive Consistency IOWA (AC-IOWA) operator U [12,29,60] able to operate with fuzzy and linguistic preference relations is used:”
Some induced ordered weighted averaging operators and their use for solving group decision-making problems based on fuzzy preference relations (2007, methodology): “In this paper we will focus on the aggregation of numerical preferences, which is why we assume that the nature of the first argument of the IOWA operators is also numeric, although it could be linguistic [26–29].”
Induced uncertain linguistic OWA operators applied to group decision making (2006, background): “Yager [6] suggests a number of applications of the IOWA aggregation operators, and extends the idea of order induced aggregation to the Choquet aggregation resulting in what he calls the induced Choquet ordered averaging (I-COA) operator.”
Induced generalized intuitionistic fuzzy operators (2011, methodology): “Based on Definition 1 and the idea of order induced aggregation [40,41], in the following, we utilize the Choquet integral to develop some generalized aggregation operators for IFVs.”
A Consensus Model for Group Decision Making With Incomplete Fuzzy Preference Relations (2007, methodology): “Additionally, we also introduce an Induced Ordered Weighted Averaging (IOWA) operator [31], [42]–[44] to aggregate the experts’ preferences in the whole decision process which uses both consensus and consistency criteria as inducing variable.”