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Granular Computing
Erschienen in: Granular Computing 1/2020

07.09.2018 | Original Paper

Hybrid models for decision-making based on rough Pythagorean fuzzy bipolar soft information

verfasst von: Muhammad Akram, Ghous Ali

Erschienen in: Granular Computing | Ausgabe 1/2020

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Abstract

A Pythagorean fuzzy set model is a powerful tool for depicting fuzziness and uncertainty. In this paper, the notions of two novel hybrid models, namely Pythagorean fuzzy bipolar soft set model and rough Pythagorean fuzzy bipolar soft set model are introduced. The Pythagorean fuzzy bipolar soft set is the generalization of different hybrid models including bipolar soft set, fuzzy bipolar soft set and the Pythagorean fuzzy soft set. Our developed concepts are illustrated by examples. Some useful basic properties and operations of the hybrid models are investigated. In particular, multiattribute decision-making problems with numerical examples are solved by our new hybrid models. An algorithm of each approach is developed.
Nächster Artikel Computation of generalized linguistic term sets based on fuzzy logical algebras for multi-attribute decision making

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Metadaten
Titel
Hybrid models for decision-making based on rough Pythagorean fuzzy bipolar soft information
verfasst von
Muhammad Akram
Ghous Ali
Publikationsdatum
07.09.2018
Verlag
Springer International Publishing
Erschienen in
Granular Computing / Ausgabe 1/2020
Print ISSN: 2364-4966
Elektronische ISSN: 2364-4974
DOI
https://doi.org/10.1007/s41066-018-0132-3

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