Neutrosophic fusion of rough set theory: An overview

Zhang, Chao; Li, Deyu; Kang, Xin; Song, Duheon; Sangaiah, Arun Kumar; Broumi, Said

doi:10.1016/j.compind.2019.07.007

Cited by 41 publications

(26 citation statements)

References 90 publications

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“…To handle MAGDM information fusion and analysis with IN information effectively, GrC-based approaches own unique superiorities in constructing problem addressing approaches via multi-view problem solving tactics [23,24]. During the past several years, taking full advantage of GrC-based approaches, many scholars and practitioners have obtained fruitful results in merging NSs with rough sets [25][26][27][28][29][30][31][32], formal concept analysis [33,34], three-way decisions [35][36][37], and others [38,39]. In the current article, we plan to propose a new IN MAGDM method via multigranulation probabilistic models, which can provide a risk-based information synthesis scheme with the capability of error tolerance in light of GrC-based approaches.…”

Section: A Brief Review Of Multigranulation Probabilistic Modelsmentioning

confidence: 99%

Multi-Attribute Group Decision Making Based on Multigranulation Probabilistic Models with Interval-Valued Neutrosophic Information

Zhang

Kang

et al. 2020

Mathematics

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In plenty of realistic situations, multi-attribute group decision-making (MAGDM) is ubiquitous and significant in daily activities of individuals and organizations. Among diverse tools for coping with MAGDM, granular computing-based approaches constitute a series of viable and efficient theories by means of multi-view problem solving strategies. In this paper, in order to handle MAGDM issues with interval-valued neutrosophic (IN) information, we adopt one of the granular computing (GrC)-based approaches, known as multigranulation probabilistic models, to address IN MAGDM problems. More specifically, after revisiting the related fundamental knowledge, three types of IN multigranulation probabilistic models are designed at first. Then, some key properties of the developed theoretical models are explored. Afterwards, a MAGDM algorithm for merger and acquisition target selections (M&A TSs) with IN information is summed up. Finally, a real-life case study together with several detailed discussions is investigated to present the validity of the developed models.

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Section: A Brief Review Of Multigranulation Probabilistic Modelsmentioning

confidence: 99%

Multi-Attribute Group Decision Making Based on Multigranulation Probabilistic Models with Interval-Valued Neutrosophic Information

Zhang

Kang

et al. 2020

Mathematics

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“…At the same time, as the IFS theory gradually matures, its limitations gradually appear. erefore, many scholars are committed to the expansion and development of IFS theory, and various expansion forms and their applications have been proposed, such as pythagorean fuzzy set theory [10][11][12][13][14][15][16], intuitionistic cubic fuzzy set theory [17], neutrosophic set theory [18][19][20][21][22], and so on.…”

Section: Introductionmentioning

confidence: 99%

Picture Fuzzy TOPSIS Method Based on CPFRS Model: An Application to Risk Management Problems

Zhao

You

2021

Scientific Programming

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It is not widely acknowledged that multicriteria decision-making (MCDM) problems in some particular circumstances cannot be effectively solved by some traditional methods. This paper aims to construct a novel decision-making method to effectively solve these MCDM problems. Firstly, we propose a covering-based picture fuzzy rough set (CPFRS) model by combining the picture fuzzy (PF) neighborhood operator and some PF logical operators. Secondly, by combining the proposed CPFRS model with the principle of TOPSIS method, a new method is proposed to solve the MCDM problems under PF environments. Finally, we apply our proposed method to the risk management of green buildings. By comparing the proposed method with some existing MCDM methods, the established method is effective and flexible and can be applied to a wide range of environments.

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“…Gulistan and Salma [25] discussed the application of neutrosophic logic using complex fuzzy sets. More information about neutrosophic logic can be seen in Yang [55], Peng and Dai [42], Zhang et al [58], and Zhang et al [59].…”

Section: Introductionmentioning

confidence: 99%

Single-stage and two-stage total failure-based group-sampling plans for the Weibull distribution under neutrosophic statistics

Aslam

Rao

Khan

2021

Complex Intell. Syst.

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If the sample or population has vague, inaccurate, unidentified, deficient, indecisive, or fuzzy data, then the available sampling plans could not be suitable to use for decision-making. In this article, an improved group-sampling plan based on time truncated life tests for Weibull distribution under neutrosophic statistics (NS) has been developed. We developed improved single and double group-sampling plans based on the NS. The proposed design neutrosophic plan parameters are obtained by satisfying both producer’s and consumer’s risks simultaneously under neutrosophic optimization solution. Tables are constructed for the selected shape parameter of Weibull distribution and various combinations of neutrosophic group size. The efficiency of the proposed group-sampling plan under the neutrosophic statistical interval method is also compared with the crisp method grouped sampling plan under classical statistics.

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Neutrosophic fusion of rough set theory: An overview

Cited by 41 publications

References 90 publications

Multi-Attribute Group Decision Making Based on Multigranulation Probabilistic Models with Interval-Valued Neutrosophic Information

Multi-Attribute Group Decision Making Based on Multigranulation Probabilistic Models with Interval-Valued Neutrosophic Information

Picture Fuzzy TOPSIS Method Based on CPFRS Model: An Application to Risk Management Problems

Single-stage and two-stage total failure-based group-sampling plans for the Weibull distribution under neutrosophic statistics

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