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首页> 外文期刊>Knowledge-Based Systems >Inclusion measure-based multi-granulation intuitionistic fuzzy decision-theoretic rough sets and their application to ISSA
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Inclusion measure-based multi-granulation intuitionistic fuzzy decision-theoretic rough sets and their application to ISSA

机译：基于包含度量的多粒度直觉模糊决策理论粗糙集及其在ISSA中的应用

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Decision-theoretic rough set (DTRS) and multi-granulation rough set (MGRS) are two important extended types of Pawlak's classical rough set model. The two generalized rough sets have been investigated separately by numerous researchers. However, few studies have focused on the combination of the two rough sets in intuitionistic fuzzy (IF) settings. In this study, two novel MG-IF-DTRS models, which are generalizations of MG-DTRSs, are developed by exploring DTRS and MGRS based on IF inclusion measures to explore multi-granulation IF DTRS (MG-IF-DTRS) under IF information environment. We introduce a type of inclusion measure between two IF sets and present the concept of inclusion measure-based IF-DTRS. We verify whether the model is an extension of the classical DTRS. Second, we present the inclusion measure-based optimistic and pessimistic MG-IF-DTRSs, analyze their properties, and conclude that the presented MG-IF-DTRSs are generalizations of MG-DTRSs from the viewpoint of multi-granulation. We then study the discernibility-function-based reduction methods for the presented MG-IF-DTRSs. We also provide an illustrative example of information system security audit to verify the established approach and demonstrate its validity and applicability. Finally, we discuss several possible generalizations related to MG-IF-DTRSs. This study provides a MG-IF-DTRS method for acquiring knowledge from multi granulation IF decision systems. (C) 2017 Elsevier B.V. All rights reserved.
机译：决策理论粗糙集（DTRS）和多粒度粗糙集（MGRS）是Pawlak经典粗糙集模型的两个重要扩展类型。许多研究人员分别对这两个广义粗糙集进行了研究。但是，很少有研究集中在直觉模糊（IF）设置中两个粗糙集的组合上。在这项研究中，通过探索DTRS和MGRS基于IF包含措施，在IF信息下探索多粒IF DTRS（MG-IF-DTRS），开发了两种新颖的MG-IF-DTRS模型，即MG-DTRS的推广。环境。我们介绍了两个IF集之间的一种包含度量，并介绍了基于包含度量的IF-DTRS的概念。我们验证该模型是否是经典DTRS的扩展。其次，我们提出了基于包容性的乐观和悲观的MG-IF-DTRSs，分析了它们的性质，并得出结论，从多粒度的角度出发，提出的MG-IF-DTRSs是MG-DTRSs的推广。然后，我们研究了针对提出的MG-IF-DTRS的基于区分功能的归约方法。我们还提供了信息系统安全审核的说明性示例，以验证所建立的方法并证明其有效性和适用性。最后，我们讨论了与MG-IF-DTRS相关的几种可能的概括。这项研究提供了一种MG-IF-DTRS方法，用于从多颗粒中频决策系统中获取知识。 （C）2017 Elsevier B.V.保留所有权利。

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