Results 151 to 160 of about 1,366,394 (188)

Ranking of alternatives with ordered weighted averaging operators

International Journal of Intelligent Systems, 2004
Summary: Multiattribute decision making is an important part of the decision process for both individual and group problems. We incorporate the fuzzy set theory and the basic nature of subjectivity due to ambiguity to achieve a flexible decision approach suitable for uncertain and fuzzy environments.
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Multiple priorities in an induced ordered weighted averaging operator

International Journal of Intelligent Systems, 2000
Summary: The Ordered Weighted 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.
H. B. Mitchell, P. A. Schaefer
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SIMILARITY CLASSIFIER WITH WEIGHTED ORDERED WEIGHTED AVERAGING OPERATOR

FUZZY ECONOMIC REVIEW, 2016
(ProQuest: ... denotes formulae omitted.)1.INTRODUCTIONVast amount of data produced by computers and the internet of things and the increased ability to create automated systems have led to a growing need for effective ways to monitor performance and to detect problems, monitoring and problem detection are often linked to classification as states of ...
O. Kurama, P. Luukka, M. Collan
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Ordered Weighted Averaging Operators: A Short Review

IEEE Systems, Man, and Cybernetics Magazine, 2021
Aggregation is the process of combining several numerical values into a single representative one, a procedure called an aggregation function . Despite the simplicity of this definition, the size of the field of its applications is incredibly huge. Making decisions (in also artificial intelligence) often leads to aggregating preferences or scores on ...
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Aggregation of ordinal data using ordered weighted averaging operator weights

Annals of Operations Research, 2012
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Byeong Seok Ahn, Sang Hyun Choi
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On ordered weighted averaging aggregation operators in multicriteria decisionmaking

IEEE Transactions on Systems, Man, and Cybernetics, 1988
Summary: We are primarily concerned with the problem of aggregating multicriteria to form an overall decision function. We introduce a new type of operator for aggregation called an ordered weighted aggregation (OWA) operator. We investigate the properties of this operator.
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Induced Ordered Weighted Averaging Operators

2011
Since the introduction of the ordered weighted averaging operator [18], the OWA has received great attention with applications in fields including decision making, recommender systems [8, 21], classification [10] and data mining [16] among others. The most important step in the calculation of the OWA is the permutation of the input vector according to ...
Gleb Beliakov, Simon James
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Majority additive-ordered weighting averaging: A new neat ordered weighting averaging operator based on the majority process

Int. J. Intell. Syst., 2003
Summary: A problem that we had encountered in the aggregation process is how to aggregate the elements that have cardinality greater than one. The most common operators used in the aggregation process produce reasonable results, but, at the same time, when the items to aggregate have cardinality greater than one, they may produce distributed problems ...
José Ignacio Peláez, Jesús M. Doña
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On Prioritized 2-tuple Ordered Weighted Averaging Operators

2012
This paper deals with linguistic aggregation problems where there exists a prioritization relationship over attributes. We propose a prioritized 2-tuple ordered weighted averaging (PTOWA) operator and study its properties. We then use this operator and a TOWA operator to aggregate satisfactions of attributes for alternatives.
Cui-Ping Wei, Xijin Tang 0001, Xiaojie Wang   +2 more
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Domination of ordered weighted averaging operators over t-norms

Soft Computing, 2003
The paper contributes to the theoretical background of applications of fuzzy logics and fuzzy systems to the processing of data on the base of the strongest t-norms. It is known that some of the applications lead to complications connected with the increase of uncertainty.
Radko Mesiar, Susanne Saminger
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