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

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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.

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Funding

This work is supported by The Natural Science Foundation of Hebei Province (F2018209374) and The Natural Science Foundation of Hebei Province (F2016209344).

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Correspondence to Ruiyan Gao.

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Zhang, C., Feng, X. & Gao, R. Three-way decision models and its optimization based on Dempster–Shafer evidence theory and rough sets. Granul. Comput. 6, 411–420 (2021). https://doi.org/10.1007/s41066-019-00201-6

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  • DOI: https://doi.org/10.1007/s41066-019-00201-6

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