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Multi-granulation fuzzy decision-theoretic rough sets and bipolar-valued fuzzy decision-theoretic rough sets and their applications

机译:多粒状模糊决策 - 理论粗糙集和双极性模糊决策 - 理论粗糙集及其应用

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摘要

This paper investigates the decision-theoretic rough set (DTRS) approach in the frameworks of multi-granulation fuzzy and bipolar-valued fuzzy (BVF) probabilistic approximation spaces, respectively. By integrating fuzzy probability and BVF probability into the Bayesian decision procedure, we get four types of model of multi-granulation fuzzy decision-theoretic rough set (MG-FDTRS) approach and multi-granulation bipolar-valued fuzzy decision-theoretic rough set (MG-BVF-DTRS) approach. Our four types of model of the MG-FDTRS and the MG-BVF-DTRS approaches are mainly based on computation of the four different conditional probabilities within the frameworks of multi-granulation fuzzy and BVF probabilistic approximation spaces, respectively. The main contribution of this paper is twofold. One is to extend the fuzzy decision-theoretic rough set (FDTRS) approach to the MG-FDTRS and the MG-BVF-DTRS approaches. Another is to address its applicable ability as it is applied to deal with the multi-source fuzzy and BVF probabilistic decision systems. An example is included to show the feasibility and potential results obtained.
机译:本文分别研究了多粒状模糊和双极性模糊(BVF)概率逼近空间的框架中的决策 - 理论粗糙集(DTRS)方法。通过将模糊概率和BVF概率集成到贝叶斯决策程序中,我们获得四种类型的多粒状模糊决策 - 理论粗糙集(MG-FDTRS)方法和多粒状双极性模糊决策 - 理论粗糙集(MG -bvf-dtrs)方法。我们的四种类型的MG-FDTRS和MG-BVF-DTRS方法主要基于计算多粒状模糊和BVF概率近似空间框架内的四种不同条件概率的计算。本文的主要贡献是双重的。一个是将模糊决策 - 理论粗糙集(FDTRS)方法扩展到MG-FDTRS和MG-BVF-DTRS方法。另一种是解决其适用的能力,因为它适用于处理多源模糊和BVF概率决策系统。包括一个示例以显示所获得的可行性和潜在结果。

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