Results 21 to 30 of about 938,087 (184)

A New Minkowski Distance Based on Induced Aggregation Operators [PDF]

open access: yesInternational Journal of Computational Intelligence Systems, 2011
The Minkowski distance is a distance measure that generalizes a wide range of distances such as the Hamming and the Euclidean distance. In this paper, we develop a generalization of the Minkowski distance by using the induced ordered weighted averaging ...
José Merigo, Montserrat Casanovas
doaj   +1 more source

Decision Support under Risk by Optimization of Scenario Importance Weighted OWA Aggregations

open access: yesJournal of Telecommunications and Information Technology, 2023
The problem of evaluation outcomes under several scenarios to form overall objective functions is of considerable importance in decision support under uncertainty. The fuzzy operator defined as the so-called weighted OWA (WOWA) aggregation offers a well-
Włodzimierz Ogryczak   +1 more
doaj   +1 more source

Decision making with Dempster-Shafer belief structure and the OWAWA operator

open access: yesTechnological and Economic Development of Economy, 2014
A new decision making model that uses the weighted average and the ordered weighted averaging (OWA) operator in the Dempster-Shafer belief structure is presented.
José M. Merigo   +2 more
doaj   +1 more source

Least Squares in a Data Fusion Scenario via Aggregation Operators

open access: yesAxioms, 2022
In this paper, appropriate least-squares methods were developed to operate in data fusion scenarios. These methods generate optimal estimates by combining measurements from a finite collection of samples.
Gildson Queiroz de Jesus   +1 more
doaj   +1 more source

An Iterative Approach for the Solution of the Constrained OWA Aggregation Problem with Two Comonotone Constraints

open access: yesInformation, 2022
In this paper, first, we extend the analytical expression of the optimal solution of the constrained OWA aggregation problem with two comonotone constraints by also including the case when the OWA weights are arbitrary non-negative numbers.
Lucian Coroianu, Robert Fullér
doaj   +1 more source

Fuzzy Branch-and-Bound Algorithm with OWA Operators in the Case of Consumer Decision Making

open access: yesMathematics, 2021
The ordered weighted averaging (OWA) operator is one of the most used techniques in the operator’s aggregation procedure. This paper proposes a new assignment algorithm by using the OWA operator and different extensions of it in the Branch-and-bound ...
Emili Vizuete-Luciano   +4 more
doaj   +1 more source

A Partial Order OWA Operator for Solving the OWA Weighing Dilemma

open access: yesIEEE Access, 2023
Prior weights are necessary for the application of ordered weighted averaging (OWA) operators, but obtaining them is expensive and contentious, which restricts the application of operators.
Mingyu Li, Ruize Xu, Qinghua Chen
doaj   +1 more source

Uncertain group decision-making with induced aggregation operators and Euclidean distance

open access: yesTechnological and Economic Development of Economy, 2013
In this paper, we present the induced uncertain Euclidean ordered weighted averaging distance (IUEOWAD) operator. It is an extension of the OWA operator that uses the main characteristics of the induced OWA (IOWA), the Euclidean distance and uncertain ...
Weihua Su, Shouzhen Zeng, Xiaojia Ye
doaj   +1 more source

Intuitionistic fuzzy generalized probabilistic ordered weighted averaging operator and its application to group decision making

open access: yesTechnological and Economic Development of Economy, 2016
In this paper, we present the intuitionistic fuzzy generalized probabilistic ordered weighted averaging (IFGPOWA) operator. It is a new aggregation operator that uses generalized means in a unified model between the probability and the OWA operator.
Shouzhen Zeng, Weihua Su, Chonghui Zhang
doaj   +1 more source

OWA-FRPS: A Prototype Selection Method Based on Ordered Weighted Average Fuzzy Rough Set Theory [PDF]

open access: yes, 2013
The Nearest Neighbor NN algorithm is a well-known and effective classification algorithm. Prototype Selection PS, which provides NN with a good training set to pick its neighbors from, is an important topic as NN is highly susceptible to noisy data. Accurate state-of-the-art PS methods are generally slow, which motivates us to propose a new PS method ...
Nele Verbiest   +2 more
openaire   +3 more sources

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