Results 161 to 170 of about 70,164 (185)
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Soft Computing - A Fusion of Foundations, Methodologies and Applications, 1999
The basic properties of the Ordered Weighted Averaging (OWA) operator are recalled. The role of these operators in the formulation of multi-criteria decision functions, using the concept of quantifier guided aggregation, is discussed. An extended class of OWA operators, one based upon a relaxation of the requirements on the OWA operators, is introduced.
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The basic properties of the Ordered Weighted Averaging (OWA) operator are recalled. The role of these operators in the formulation of multi-criteria decision functions, using the concept of quantifier guided aggregation, is discussed. An extended class of OWA operators, one based upon a relaxation of the requirements on the OWA operators, is introduced.
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Soft Computing, 2006
We introduce the idea of centered OWA operators. We define these as OWA operators that give preference to argument values that lie in the middle between the largest and the smallest. An important class of these using Gaussian type weights is investigated in considerable detail. We describe a number of different examples of centered OWA operators.
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We introduce the idea of centered OWA operators. We define these as OWA operators that give preference to argument values that lie in the middle between the largest and the smallest. An important class of these using Gaussian type weights is investigated in considerable detail. We describe a number of different examples of centered OWA operators.
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Probabilistically Weighted OWA Aggregation
IEEE Transactions on Fuzzy Systems, 2014In decision-making under uncertainty we have a collection of alternatives from which we must choose one. Associated with each alternative is an uncertainty profile consisting of the set of possible outcomes that can occur if we choose this alternative along with some indication of the uncertainty associated with the outcomes.
Ronald R. Yager, Naif Alajlan
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International Journal of Intelligent Systems, 1999
Summary: The Ordered Weighting Averaging (OWA) Operator of Yager was introduced to provide a method for nonlinearly aggregating a set of input arguments \(a_i\). A fundamental aspect of the OWA operator is a reordering step in which the input arguments are rearranged according to their values. Recently, a generalized OWA operator was described in which
Schaefer, P. A., Mitchell, H. B.
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Summary: The Ordered Weighting Averaging (OWA) Operator of Yager was introduced to provide a method for nonlinearly aggregating a set of input arguments \(a_i\). A fundamental aspect of the OWA operator is a reordering step in which the input arguments are rearranged according to their values. Recently, a generalized OWA operator was described in which
Schaefer, P. A., Mitchell, H. B.
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Fuzzy Optimization and Decision Making, 2009
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Generalizations of OWA Operators
IEEE Transactions on Fuzzy Systems, 2015OWA operators can be seen as symmetrized weighted arithmetic means, as Choquet integrals with respect to symmetric measures, or as comonotone additive functionals. Following these three different looks on OWAs, we discuss several already known generalizations of OWA operators, including GOWA, IOWA, OMA operators, as well as we propose new types of such
Radko Mesiar +2 more
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International Journal of Intelligent Systems, 2002
Summary: The Ordered Weighted Averaging (OWA) operator was introduced by Yager 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 ...
Xu, Z. S., Da, Q. L.
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Summary: The Ordered Weighted Averaging (OWA) operator was introduced by Yager 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 ...
Xu, Z. S., Da, Q. L.
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IEEE Transactions on Fuzzy Systems, 2018
Inspired by the real needs of group decision problems, aggregation of ordered weighted averaging (OWA) operators is studied and discussed. Our results can be applied for data acting on any real interval, such as the standard scales $[0,1]$ and $[0,\infty [$ , bipolar scales $[-1,1]$ and $\mathbb {R}=]-\infty, \infty [$ , etc.
Radko Mesiar +3 more
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Inspired by the real needs of group decision problems, aggregation of ordered weighted averaging (OWA) operators is studied and discussed. Our results can be applied for data acting on any real interval, such as the standard scales $[0,1]$ and $[0,\infty [$ , bipolar scales $[-1,1]$ and $\mathbb {R}=]-\infty, \infty [$ , etc.
Radko Mesiar +3 more
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International Journal of Intelligent Systems, 1997
Summary: One of the properties that the OWA operator satisfies is commutativity. This condition, that is not satisfied by the weighted mean, stands for equal reliability of all the information sources that supply the data. In this article we define a new combination function, the WOWA (weighted OWA), that combines the advantages of the OWA operator and
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Summary: One of the properties that the OWA operator satisfies is commutativity. This condition, that is not satisfied by the weighted mean, stands for equal reliability of all the information sources that supply the data. In this article we define a new combination function, the WOWA (weighted OWA), that combines the advantages of the OWA operator and
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2006
Yager [1] introduced several families of ordered weighted averaging (OWA) operators, in which the associated weights depend on the aggregated arguments. In this paper, we develop a new dependent OWA operator, and study some of its desirable properties.
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Yager [1] introduced several families of ordered weighted averaging (OWA) operators, in which the associated weights depend on the aggregated arguments. In this paper, we develop a new dependent OWA operator, and study some of its desirable properties.
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