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A note on weights vector of ordered weighted averaging aggregation
2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), 2015This note has two purposes. One is to give a new weight vector W(n)=(w1(n),w2(n),…,wn(n))T for ordered weighted averaging aggregation. This weight vector possesses a peculiar feature: for each i, the weight wi tends to 0 whenever n tends to ∞, but orness(W) tends to 1.
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Variances with Bonferroni means and ordered weighted averages
International Journal of Intelligent Systems, 2019The variance is a statistical measure frequently used for analysis of dispersion in the data. This paper presents new types of variances that use Bonferroni means and ordered weighted averages in the aggregation process of the variance. The main advantage of this approach is that we can underestimate or overestimate the variance according to the ...
Fabio Blanco-Mesa +3 more
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An Ordered Weighted Average with a Truncation Weight on Intervals
2012This paper deals with ordered weighted averages on a closed interval, and their fundamental properties are investigated. In this paper we focus on ordered weighted average with a truncation weight, and the sub-additivity of a top-concentrated average is derived. Several examples are given to understand the idea.
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The ordered weighted average corporate social responsibility
Kybernetes, 2019PurposeThe purpose of this paper is to identify new formulations for evaluating corporate social responsibility using different aggregation information operators.Design/methodology/approachThe ordered weighted average (OWA) operator and its extensions, the induced OWA (IOWA) and prioritized OWA (POWA) operators are used to generate a new score for a ...
Marlenne G. Velazquez-Cazares +3 more
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The Unbalanced Linguistic Ordered Weighted Averaging operator
International Conference on Fuzzy Systems, 2010Aggregation operators for linguistic variables usually assume a uniform and symmetrical distribution of the linguistic terms that define the variable. A well-known aggregation operator is the Linguistic Ordered Weighted Average (LOWA), which has been extensively applied.
David Isern +3 more
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Density-induced ordered weighted averaging operators
International Journal of Intelligent Systems, 2011We provide a special type of induced ordered weighted averaging (OWA) operator called density-induced OWA (DIOWA) operator, which takes the density around the arguments as the inducing variables to reorder the arguments. The density around the argument, which can measure the degree of similarity between the argument and its nearest neighbors, is ...
Feng-Mei Ma, Ya-Jun Guo
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Ordered Novel Weighted Averages
2018The novel weighted averages (NWAs) are extensions of the linear arithmetic weighted average and are powerful tools in aggregating diverse inputs including numbers, intervals, type-1 fuzzy sets (T1 FSs), words modeled by interval type-2 fuzzy sets, or a mixture of them.
Dongrui Wu, Jian Huang
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Similarity classifier with ordered weighted averaging operators
Expert Systems with Applications, 2013In this article we extend the similarity classifier to cover also ordered weighted averaging (OWA) operators. Earlier, similarity classifier was mainly used with generalized mean operator, but in this article we extend this aggregation process to cover more general OWA operators.
Pasi Luukka, Onesfole Kurama
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Ranking of alternatives with ordered weighted averaging operators
International Journal of Intelligent Systems, 2004Summary: 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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A Generalization of the Variance by Using the Ordered Weighted Average
2013The ordered weighted average is an aggregation operator that provides a parameterized family of aggregation operators between the minimum and the maximum. This paper analyzes the use of the ordered weighted average in the variance. It presents several extensions by using a unified framework between the weighted average and the ordered weighted average.
José M. Merigó +2 more
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