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Erschienen in: International Journal of Machine Learning and Cybernetics 6/2016

01.12.2016 | Original Article

Interval valued hesitant fuzzy uncertain linguistic aggregation operators in multiple attribute decision making

verfasst von: Guiwu Wei

Erschienen in: International Journal of Machine Learning and Cybernetics | Ausgabe 6/2016

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Abstract

In this paper, we investigate the multiple attribute decision making problem based on the arithmetic and geometric aggregation operators with interval valued hesitant fuzzy uncertain linguistic information. Then, motivated by the ideal of traditional arithmetic and geometric operation, we shall develop some aggregation operators for aggregating interval valued hesitant fuzzy uncertain linguistic information: interval valued hesitant fuzzy uncertain linguistic arithmetic aggregation operators, interval valued hesitant fuzzy uncertain linguistic geometric aggregation operators, interval valued hesitant fuzzy uncertain linguistic correlated aggregation operators, induced interval valued hesitant fuzzy uncertain linguistic aggregation operators, induced interval valued hesitant fuzzy uncertain linguistic correlated aggregation operators, interval valued hesitant fuzzy uncertain linguistic prioritized aggregation operators, interval valued hesitant fuzzy uncertain linguistic power aggregation operators. The prominent characteristic of these proposed operators are studied. Then, we shall utilize these operators to develop some approaches to solve the interval valued hesitant fuzzy uncertain linguistic multiple attribute decision making problems. Finally, a practical example is given to verify the developed approach and to demonstrate its practicality and effectiveness.

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Metadaten
Titel
Interval valued hesitant fuzzy uncertain linguistic aggregation operators in multiple attribute decision making
verfasst von
Guiwu Wei
Publikationsdatum
01.12.2016
Verlag
Springer Berlin Heidelberg
Erschienen in
International Journal of Machine Learning and Cybernetics / Ausgabe 6/2016
Print ISSN: 1868-8071
Elektronische ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-015-0433-7

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