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Fuzzy and interval-valued fuzzy decision-theoretic rough set approaches based on fuzzy probability measure

机译：基于模糊概率测度的模糊区间值模糊决策理论粗糙集方法

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This paper investigates decision-theoretic rough set (DTRS) approach in the frameworks of fuzzy and interval-valued fuzzy (IVF) probabilistic approximation spaces, respectively. It takes fuzzy probability and IVF probability into consideration. Bayesian decision procedure is a basis of DTRS approach. By integrating fuzzy probability measure and IVF probability measure into Bayesian decision procedure, there come fuzzy decision-theoretic rough set (FDTRS) approach and interval-valued fuzzy decision-theoretic rough set (IVF-DTRS) approach. The new approaches have the ability to directly deal with real-valued and interval-valued data. This makes FDTRS and IVF-DTRS more applicable than DTRS. Two methods are presented to compare intervals while constructing the IVF-DTRS approach: one is compatible with DTRS and FDTRS approaches; the other is a total order based on which the decision procedure is much easier to operate. Cases of two different universes of discourse for FDTRS and IVF-DTRS are also taken into account. (C) 2014 Elsevier Inc. All rights reserved.
机译：本文分别研究了模糊和区间值模糊（IVF）概率近似空间框架中的决策理论粗糙集（DTRS）方法。它考虑了模糊概率和IVF概率。贝叶斯决策程序是DTRS方法的基础。通过将模糊概率测度和IVF概率测度集成到贝叶斯决策过程中，形成了模糊决策理论粗糙集（FDTRS）方法和区间值模糊决策理论粗糙集（IVF-DTRS）方法。新方法具有直接处理实值和间隔值数据的能力。这使得FDTRS和IVF-DTRS比DTRS更适用。在构建IVF-DTRS方法时，提出了两种比较时间间隔的方法：一种与DTRS和FDTRS方法兼容。另一个是总订单，基于此订单的决策程序更容易操作。还考虑了FDTRS和IVF-DTRS的两种不同话语范围。 （C）2014 Elsevier Inc.保留所有权利。

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