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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 12/2019

01.01.2019 | Original Article

Belief structure-based induced aggregation operators in decision making with hesitant fuzzy information

verfasst von: Xihua Li, Xiaohong Chen

Erschienen in: Neural Computing and Applications | Ausgabe 12/2019

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Abstract

In this paper, the decision-making problems under hesitant fuzzy environment are investigated with Dempster–Shafer (D–S) theory. Firstly, some basic concepts of hesitant fuzzy sets, generalized hesitant fuzzy sets and D–S theory are introduced. Then two new aggregation operators: belief structure hesitant fuzzy induced ordered weighted averaging operator and belief structure hesitant fuzzy induced ordered weighted geometric operator are developed, and some properties of the proposed operators are studied. A belief structure hesitant fuzzy induced aggregation operators-based decision-making approach under uncertainty is developed. Then the proposed operators and procedures are extended to generalized hesitant fuzzy environment. Finally, some illustrative examples show the feasibility of the proposed methods.
Vorheriger Artikel Multi-criteria decision-making with probabilistic hesitant fuzzy information based on expected multiplicative consistency
Nächster Artikel Dilated residual attention network for load disaggregation

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Metadaten
Titel
Belief structure-based induced aggregation operators in decision making with hesitant fuzzy information
verfasst von
Xihua Li
Xiaohong Chen
Publikationsdatum
01.01.2019
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 12/2019
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-018-3947-6

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