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Granular Computing

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25.04.2018 | Original Paper

Quasiconvex possibility distribution with application in decision-making

verfasst von: Lesheng Jin, Jian Wang, Gang Qian

Erschienen in: Granular Computing | Ausgabe 2/2019

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Abstract

Possibility distribution was originally introduced by Negoita et al. (Fuzzy Sets Syst 1:61–72, 1978), which has some relation to fuzzy sets while has its own practical meaning. During more than three decades, it has some developments especially in theoretical studies. As an alternative way to model uncertainty, possibility theory has its own advantages just as fuzzy sets did. In this study, we review the concepts of possibility distribution and propose quasiconvex possibility distribution with their mathematical properties and applications. Together with some properties of them, we also put emphasis on their special application cases in decision-making practices. Throughout this study, we propose several new concepts and definitions with reasonable illustrative examples, from which it can be seen that quasiconvex possibility distributions are powerful tools and can be widely used in other applications.

Vorheriger Artikel Pythagorean fuzzy prioritized aggregation operators and their application to multi-attribute group decision making

Nächster Artikel Granular computing-based approach of rule learning for binary classification

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Titel: Quasiconvex possibility distribution with application in decision-making
verfasst von: Lesheng Jin
Jian Wang
Gang Qian
Publikationsdatum: 25.04.2018
Verlag: Springer International Publishing
Erschienen in: Granular Computing / Ausgabe 2/2019
Print ISSN: 2364-4966
Elektronische ISSN: 2364-4974
DOI: https://doi.org/10.1007/s41066-018-0096-3

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