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Determining Three-Way Decisions With Decision-Theoretic Rough Sets Using a Relative Value Approach

机译:使用相对值方法用决策理论粗糙集确定三路决策

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Three-way decisions play an important role in rough sets and decision theory. As a representative model, decision-theoretic rough sets (DTRSs) provide a sound interpretation of thresholds used in three-way decisions. This problem is associated with the determination of the loss function of DTRSs. In this paper, we investigate a novel way of determining the loss functions of DTRSs with relative values. More specifically, with the aid of analytic hierarchy process (AHP) method, the determination of loss functions is realized in the context of DTRSs. First, a hierarchical structure of DTRSs is constructed. Second, along the hierarchical structure, pairwise comparison matrices are analyzed in a top-down fashion. In light of the generic condition imposed on the loss functions of DTRSs, some constraints on relative values between loss functions are introduced. The relative ratios at each level are computed. Considering the consistency ratio (CR) of the reciprocal matrices, two mathematical programming approaches are developed by exploiting the flexibility of information granularity. Then, we design a decision procedure for the determination of loss functions and deduce three-way decisions. The loss functions are calculated by aggregating the relative ratios being available at each level. With regard to the loss functions, we finally compare the existing studies with the AHP method. We demonstrate that the relative value with AHP improves the restriction of the existing studies and exhibits a certain level of tolerance to inconsistency.
机译:三路决策在粗糙集和决策理论中起着重要作用。作为代表性模型,决策理论粗糙集(DTRS)提供了对三路决策中使用的阈值的合理解释。此问题与确定DTRS的损失函数有关。在本文中,我们研究了一种确定具有相对值的DTRS损失函数的新颖方法。更具体地说,借助于层次分析法(AHP),可以在DTRS的背景下确定损失函数。首先,构建了DTRS的层次结构。其次,沿着层次结构,以自上而下的方式分析成对比较矩阵。根据DTRS损失函数的一般条件,引入了对损失函数之间相对值的一些约束。计算每个级别的相对比率。考虑到倒数矩阵的一致性比率(CR),通过利用信息粒度的灵活性,开发了两种数学编程方法。然后,我们设计了确定损失函数的决策程序,并得出了三项决策。损失函数是通过汇总每个级别可用的相对比率来计算的。关于损失函数,我们最终将现有研究与AHP方法进行比较。我们证明与AHP的相对价值改善了现有研究的局限性,并表现出一定程度的对不一致的容忍度。

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