Two Types of Intuitionistic Fuzzy Covering Rough Sets and an Application to Multiple Criteria Group Decision Making

Wang, Jingqian; Zhang, Xiaohong

doi:10.3390/sym10100462

Cited by 19 publications

(7 citation statements)

References 42 publications

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“…In application, they have been applied to knowledge reduction [10,11], decision rule synthesis [12,13], and other fields [14,15]. In theory, covering-based rough set theory has been connected with matroid theory [16][17][18], lattice theory [19,20], and fuzzy set theory [21][22][23]. Zadeh's fuzzy set theory [24] addresses the problem of how to understand and manipulate imperfect knowledge.…”

Section: Introductionmentioning

confidence: 99%

A New Type of Single Valued Neutrosophic Covering Rough Set Model

Wang

Zhang

2019

Symmetry

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Recently, various types of single valued neutrosophic (SVN) rough set models were presented based on the same inclusion relation. However, there is another SVN inclusion relation in SVN sets. In this paper, we propose a new type of SVN covering rough set model based on the new inclusion relation. Furthermore, the graph and matrix representations of the new SVN covering approximation operators are presented. Firstly, the notion of SVN β 2 -covering approximation space is proposed, which is decided by the new inclusion relation. Then, a type of SVN covering rough set model under the SVN β 2 -covering approximation space is presented. Moreover, there is a corresponding SVN relation rough set model based on a SVN relation induced by the SVN β 2 -covering, and two conditions under which the SVN β 2 -covering can induce a symmetric SVN relation are presented. Thirdly, the graph and matrix representations of the new SVN covering rough set model are investigated. Finally, we propose a novel method for decision making (DM) problems in paper defect diagnosis under the new SVN covering rough set model.

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Section: Introductionmentioning

confidence: 99%

A New Type of Single Valued Neutrosophic Covering Rough Set Model

Wang

Zhang

2019

Symmetry

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“…In application, they have been applied to knowledge reduction [6,7], decision rule synthesis [8,9], and other fields [10][11][12]. In theory, covering-based rough set theory has been connected with matroid theory [13][14][15][16], lattice theory [17,18] and fuzzy set theory [19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Two Types of Single Valued Neutrosophic Covering Rough Sets and an Application to Decision Making

Wang

Zhang

2018

Symmetry

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In this paper, to combine single valued neutrosophic sets (SVNSs) with covering-based rough sets, we propose two types of single valued neutrosophic (SVN) covering rough set models. Furthermore, a corresponding application to the problem of decision making is presented. Firstly, the notion of SVN β -covering approximation space is proposed, and some concepts and properties in it are investigated. Secondly, based on SVN β -covering approximation spaces, two types of SVN covering rough set models are proposed. Then, some properties and the matrix representations of the newly defined SVN covering approximation operators are investigated. Finally, we propose a novel method to decision making (DM) problems based on one of the SVN covering rough set models. Moreover, the proposed DM method is compared with other methods in an example.

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“…The MCDM approach was also used by Onut et al [19], in a fuzzy model with direct application in investment projects assessment. Wang and Zhang [20] proposed recently a new method for MCDM problem solving using an optimistic multi-granulation intuitionistic fuzzy rough set model, while Luo and Liang [21] created a novel similarity measure for interval-valued intuitionistic fuzzy set.…”

Section: State Of the Artmentioning

confidence: 99%

A Fuzzy Logic Algorithm for Optimizing the Investment Decisions within Companies

2019

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As companies operate in a competitive environment, where the struggle for survival on the market is rather tough, the top management face new challenges to identify methods, and even techniques, which allows it to select from the market those assets that provide an optimal ratio between the acquisition cost and the economic performance. In this context, a fuzzy logic managerial decision tool for the assets acquisition is proposed with the paper. The algorithm has three main components: the matrix of the membership degree of the existing bids to asset selection criteria, using fuzzy triangular numbers; the vector of the global membership degree of the bids to the selection criteria and the maximum of the global membership degree as an inference operator for establishing the validated bids by the algorithm. Two scenarios of asset acquisition were tested. After simulations, it was determined that the proposed fuzzy logic managerial decision tool combines, with very good results, the acquisition cost of the assets with their economic performance.

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Two Types of Intuitionistic Fuzzy Covering Rough Sets and an Application to Multiple Criteria Group Decision Making

Cited by 19 publications

References 42 publications

A New Type of Single Valued Neutrosophic Covering Rough Set Model

A New Type of Single Valued Neutrosophic Covering Rough Set Model

Two Types of Single Valued Neutrosophic Covering Rough Sets and an Application to Decision Making

A Fuzzy Logic Algorithm for Optimizing the Investment Decisions within Companies

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