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Soft Computing
Erschienen in: Soft Computing 17/2019

18.08.2018 | Methodologies and Application

Fusions and preference relations based on probabilistic interval-valued hesitant fuzzy information in group decision making

verfasst von: Shen Zhang, Zeshui Xu, Hangyao Wu

Erschienen in: Soft Computing | Ausgabe 17/2019

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Abstract

This paper proposes probabilistic interval-valued hesitant fuzzy set (P-IVHFS) by integrating the probability distribution into IVHFS. The concept can make some vital but seemingly repetitive information [such as the same memberships of interval forms given by different decision makers (DMs)], which is an important basis for decision-making rather than being discarded. Moreover, some operations and aggregation operators of probabilistic interval-valued hesitant fuzzy elements (P-IVHFEs) and probabilistic interval-valued hesitant fuzzy preference relation (P-IVHFPR) are put forward, based on which, a decision-making model is proposed. It can keep almost all information given by the DMs so that the results calculated with the model will be much more reliable than those calculated with approaches based on IVHFSs. Finally, a practical case concerning the evaluation of intelligent transportation systems is given to verify the advantages of the proposed decision-making approach based on P-IVHFPRs.
Vorheriger Artikel A dynamic local cluster ratio-based band selection algorithm for hyperspectral images
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Metadaten
Titel
Fusions and preference relations based on probabilistic interval-valued hesitant fuzzy information in group decision making
verfasst von
Shen Zhang
Zeshui Xu
Hangyao Wu
Publikationsdatum
18.08.2018
Verlag
Springer Berlin Heidelberg
Erschienen in
Soft Computing / Ausgabe 17/2019
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-018-3465-6

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