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Granular Computing
Published in: Granular Computing 2/2021

27-09-2019 | Original Paper

Three-way decision models and its optimization based on Dempster–Shafer evidence theory and rough sets

Authors: Chunying Zhang, Xiaoze Feng, Ruiyan Gao

Published in: Granular Computing | Issue 2/2021

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Abstract

Dempster–Shafer evidence, rough set and three-way decision are related to each other. They are all theories and methods of handling uncertain information. First, it is required to combine the Dempster–Shafer evidence with rough set theory, and the rough set theory can therefore be applied to obtain the basic probability assignment function of evidence, which allows it to be obtained more objectively. Second, the conditional probability function in the three-way decision is replaced by a value in the belief interval, and three-way decision models are established to integrate the Dempster–Shafer evidence theory with rough sets. Third, by adjusting the value of the belief factor, the decision inference rules suitable for decision-makers of different risk types are obtained. Finally, an example is provided in this case to prove the validity of this model.
previous article Solving I-fuzzy two person zero-sum matrix games: Tanaka and Asai approach
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Metadata
Title
Three-way decision models and its optimization based on Dempster–Shafer evidence theory and rough sets
Authors
Chunying Zhang
Xiaoze Feng
Ruiyan Gao
Publication date
27-09-2019
Publisher
Springer International Publishing
Published in
Granular Computing / Issue 2/2021
Print ISSN: 2364-4966
Electronic ISSN: 2364-4974
DOI
https://doi.org/10.1007/s41066-019-00201-6

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