A novel fuzzy rough set model with fuzzy neighborhood operators

Ye, Jin; Zhan, Jianming; Ding, Weiping; Fujita, Hamido

doi:10.1016/j.ins.2020.07.030

Cited by 112 publications

(27 citation statements)

References 46 publications

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“…From the most recent studies of SS, one can see that most of the researchers in SS theory worked on a binary evaluation {0, 1} or closed interval [0, 1] [35,36]. However, in real-world problems, we mostly find information with a non-binary yet discrete structure.…”

Section: Introductionmentioning

confidence: 99%

A novel complex fuzzy N-soft sets and their decision-making algorithm

Mahmood

Rehman

Ali

2021

Complex Intell. Syst.

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Complex fuzzy N-soft set (CFN-SS) is an important technique to manage awkward and unreliable information in realistic decision-making problems. CFN-SS is a blend of two separate theories, called N-soft sets (N-SSs) and complex fuzzy sets (CFSs), which are the modified versions of soft sets (SSs) and fuzzy sets (FSs) to depict vague and uncertain information in daily life problems. In this manuscript, the novel concept of CFN-SS is explored and their fundamental laws are discussed. CFN-SS contains the grade of truth in the form of a complex number whose real and imaginary parts are limited to the unit interval. Besides, we examine some algebraic properties for CFN-SS like union, intersections and justify these properties with the help of some numerical examples. To examine the superiority and effectiveness of the proposed approaches, the special cases of the investigated approaches are also discussed. A decision-making procedure is developed by using the investigated ideas based on CFN-SSs. Further, some numerical examples are also illustrated with the help of explored ideas to find the reliability and effectiveness of the proposed approaches. Finally, the comparative analysis of the investigated ideas with some existing ideas is also demonstrated to prove the quality of the proposed works. The graphical expressions of the obtained results are also discussed.

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Section: Introductionmentioning

confidence: 99%

A novel complex fuzzy N-soft sets and their decision-making algorithm

Mahmood

Rehman

Ali

2021

Complex Intell. Syst.

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“…In the real world, as a complex cognitive computing method, multiple attribute decision making (MADM) intends to make scientific decisions from a finite number of alternatives by utilizing the multiple attributes perspective, and then rank a series of alternatives or pursue the appropriate one through effective information aggregation rules and decision analysis tools. A lot of soft computing methods have been used for MADM research over the last decades, and most of them are addressed in the form of generalized fuzzy sets (FSs) [1,2,3,4,5]. MAGDM, an integrative research field that combines group decision-making with MADM, usually provides structures for acquiring group preference information through individual preference information and specifically evaluating various alternatives through different theoretical decision-making templates.…”

Section: Introductionmentioning

confidence: 99%

Novel Decision Making Framework Based on Complex q-Rung Orthopair Fuzzy Information

2021

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Assessing uncertainty in decision-making is a major challenge for decision makers (DMs) and the q-rung orthopair fuzzy set (q-ROFS), as the direct extension of intuitionistic fuzzy set (IFS) and pythagorean fuzzy set (PFS) play a crucial role in this aspect. The complex q-rung orthopair fuzzy set (Cq-ROFS) is a strong tool to deal with imprecision, vagueness and fuzziness by expanding the scope of membership degree (MD) and non-membership degree (NMD) of q-ROFS from real to complex unit disc. In this paper, we develop some new Cq-ROF Hamacher aggregation operators (AOs), i.e., the Cq-ROF Hamacher weighted averaging (Cq-ROFHWA) operator, the Cq-ROFH weighted geometric (Cq-ROFHWG) operator, the Cq-ROFH ordered weighted averaging (Cq-ROFHOWA) operator and the Cq-ROFH ordered weighted geometric (Cq-ROFHOWG) operator. Subsequently, we establish a novel Cq-ROF graph framework based on the Hamacher operator called Cq-ROFH graphs (Cq-ROFHGs) and evaluate its energy and Randić energy. In particular, we compute the energy of a splitting Cq-ROFHG and shadow Cq-ROFHG. Further, we describe the notions of Cq-ROFH digraphs (Cq-ROFHDGs). Moreover, an algorithm is given to solve multiple attribute group decision making (MAGDM) problems and the main steps are discussed clearly. Finally, a numerical instance related to the facade clothing systems (FCS) selection is presented to show the affectiveness of the developed concepts in decision-making circumstances. In order to verify the effectiveness of our proposed scheme, a comparative analysis with previous approaches is provided.

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“…However, the binary relation in the classical RS model is an equivalence, which is very demanding and limits the application of RS models. erefore, RS theory has been extended in many ways [58][59][60][61][62][63][64][65][66][67], among which the technology of combining FS theory, covering theory, and RS theory is an important research topic, for example, coveringbased fuzzy rough set model [61][62][63][64], covering-based intuitionistic fuzzy rough set model [65,66], covering-based spherical fuzzy rough set model [67], 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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A novel fuzzy rough set model with fuzzy neighborhood operators

Cited by 112 publications

References 46 publications

A novel complex fuzzy N-soft sets and their decision-making algorithm

A novel complex fuzzy N-soft sets and their decision-making algorithm

Novel Decision Making Framework Based on Complex q-Rung Orthopair Fuzzy Information

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

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