The uncertain OWA operator
International Journal of Intelligent SystemsPublished 25 April 2002
Zhiping Xu, Q. L. Da
Citations538
SJR quartileQ1
SJR score1.14
SNIP1.40
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
This article investigates the uncertain OWA operator in which the associated weighting parameters cannot be specified, but value ranges can be obtained and each input argument is given in the form of an interval of numerical values.
Abstract
The ordered weighted averaging (OWA) operator was introduced by Yager1 to provide a method for aggregating several inputs that lie between the max and min operators. In this article, we investigate the uncertain OWA operator in which the associated weighting parameters cannot be specified, but value ranges can be obtained and each input argument is given in the form of an interval of numerical values. The problem of ranking a set of interval numbers and obtaining the weights associated with the uncertain OWA operator is studied. © 2002 Wiley Periodicals, Inc.
Keywords
Decision SciencesMathematicsEngineering
IEEE Transactions on Systems Man and CyberneticsOn ordered weighted averaging aggregation operators in multicriteria decisionmaking
7,125 Citations1988Ronald R. Yager
A type of operator for aggregation called an ordered weighted aggregation (OWA) operator is introduced and its performance is found to be between those obtained using the AND operator and the OR operator.
Fuzzy Sets and SystemsFamilies of OWA operators
1,216 Citations1993Ronald R. Yager
A number of parametrized families of OWA operators are introduced; maximum entropy, S-OWA, step and window are among the most important of these families and the evaluation of quantified propositions using these operators is studied.
International Journal of Intelligent SystemsThe weighted OWA operator
601 Citations1997Vicenç Torra
A new combination function is defined, the WOWA (Weighted OWA), that combines the advantages of the OWA operator and the ones of the weighted mean and is study some of its properties and shows how it can be extended to deal with linguistic labels.
Fuzzy Sets and SystemsOn the issue of obtaining OWA operator weights
539 Citations1998Dimitar Filev, Ronald R. Yager
This work investigates the issue of obtaining the weights associated with the OWA aggregation in the situation when the authors have observed data on the arguments and the aggregated value and introduces a family of OWA operators called exponential OWA Operators.
Aggregating Template Or Rule Antecedents In Real-time Expert Systems With Fuzzy Set Logic
447 Citations2005Michael O'Hagan
An algorithm based on fuzzy set logic and nonlinear program- ming optimization is proposed for aggregating antecedents within a template or rule into a single valued entity for use in a detachment or implication operator for forward chaining in an expert system.
IEEE Transactions on Fuzzy SystemsCharacterization of the ordered weighted averaging operators
312 Citations1995János Fodor, Jean‐Luc Marichal +1 more
This paper deals with the characterization of two classes of monotonic and neutral (MN) aggregation operators which are stable for positive linear transformations with the same unit, independent zeroes and ordered values.
Information SciencesAnalytic properties of maximum entropy OWA operators
200 Citations1995Dimitar Filev, Ronald R. Yager
The maximum entropy approach to obtaining the weights associated with the ordered weighted averaging (OWA) aggregation operator is discussed and an analytic form for these weights are obtained and some of their properties are described.
International Journal of Man-Machine StudiesApplications and extensions of OWA aggregations
199 Citations1992Ronald R. Yager
Two possible semantics associated with the OWA operator are introduced, the first being a kind of generalized logical connective and the second being a new type of probabilistic expected value.
International Journal of General SystemsPARAMETERIZED AND-UKE AND OR-LIKE OWA OPERATORS
170 Citations1994Ronald R. Yager, Dimitar Filev
This paper discusses the OWA (Ordered Weighted Averaging) operators, and the BADD (BAsic Defuzzification Distribution) transformation, and suggests the use of the Badd transformation to generate a class of OWA like aggregation operators, denoted BADD-OWA operators, which fail to be mono-tonic.
Information SciencesMeasures of entropy and fuzziness related to aggregation operators
93 Citations1995Ronald R. Yager
Some new measures for the calculation of the entropy of a probability distribution based on the ordered weighted averaging operator and some measures of fuzziness associated with a fuzzy set are suggested.
International Journal of Uncertainty Fuzziness and Knowledge-Based SystemsA Modified OWA Operator and its Use in Lossless DPCM Image Compression
90 Citations1997H. B. Mitchell, D. D. Estrakh
An unusual application of the ordered weighted averaging operator to lossless image compression in which the input arguments are not re-arranged according to their actual relative values but ratheraccording to their estimated relative values.
International Journal of Man-Machine StudiesA general approach to criteria aggregation using fuzzy measures
61 Citations1993Ronald R. Yager
This work shows how a number of the classic aggregation methods fall out as special cases of this very general formulation based upon the use of fuzzy subsets to model the criteria and a form of the fuzzy integral to connect these two to obtain the overall decision function.
International Journal of Intelligent SystemsAn OWA operator with fuzzy ranks
38 Citations1998H. B. Mitchell, D. D. Estrakh
The OWA operator is generalized to include the case of real‐number or fuzzy ranks to provide a method for aggregating several inputs which lies between the max and min operators.
Fuzzy Sets and SystemsGeneralizing the modeling of fuzzy logic controllers by parameterized aggregation operators
32 Citations1995Ronald R. Yager, Dimitar Filev
The type of reasoning used in the typical fuzzy logic controller, the Mamdani reasoning method, is described and a method, which is called Direct Fuzzy Reasoning (DFR), which results from one choice of the parameters is introduced.
International Journal of Intelligent SystemsAn analytic characterization of some aggregation operators
23 Citations1998Sergeĭ Ovchinnikov