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On ordered weighted averaging aggregation operators in multicriteria decision-making
Ronald R. Yager
- Vol. 18, pp 183-190
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The article was published on 1988-01-01 and is currently open access. It has received 3030 citations till now. The article focuses on the topics: Ordered weighted averaging aggregation operator.read more
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A GIS-based multi-criteria decision-making approach for seismic vulnerability assessment using quantifier-guided OWA operator: a case study of Tehran, Iran
TL;DR: The main contribution of this research is to take the effect of the optimism degree into account in the problem of seismic vulnerability assessment and apply the ordered weighted averaging operator to provide a wide range of answers from pessimistic to optimistic solutions based on multi-criteria analysis.
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Induced Heavy Moving Averages
TL;DR: The induced heavy ordered weighted moving average (IHOWMA) operator is an aggregation operator that uses the main characteristics of three well‐known techniques: the moving average, induced operator, and heavy aggregation operator to provide a parameterized family of aggregation operators that include the minimum, the maximum, and total operator as special cases.
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Level sets and the extension principle for interval valued fuzzy sets and its application to uncertainty measures
TL;DR: The representation of a fuzzy subset in terms of its crisp level sets is described and its role in the extension principle and particularly to the extension of measures of uncertainty of interval valued fuzzy sets is investigated.
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Intuitionistic Fuzzy Geometric Bonferroni Means and Their Application in Multicriteria Decision Making
Wei Zhou,Jian-min He +1 more
TL;DR: This paper investigates the geometric BMs under the intuitionistic fuzzy environment, which is more common phenomenon in modern life, and develops three intuitionism fuzzy geometric Bonferroni mean operators, i.e., the IFWGBM and IFGWGBM operators.
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Child Well-Being in Rich Countries: UNICEF's Ranking Revisited, and New Symmetric Aggregating Operators Exemplified
TL;DR: The purpose is to study alternative approaches for the particular data at hand, but also to introduce and exemplify new and useful aggregation techniques: ways to select weights for OWA-operators and weighted geometric means, and how to circumvent the choice of a power for the power means.