On a novel uncertain soft set model: Z -soft fuzzy rough set model and corresponding decision making methods

Zhan, Jianming; Ali, Muhammad Irfan; Mehmood, Nayyar

doi:10.1016/j.asoc.2017.03.038

Cited by 164 publications

(36 citation statements)

References 37 publications

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“…In the future, we will apply the proposed operators ♢, , ♠, ♣, , →, $ in other fuzzy environment [26,[43][44][45][46][47][48][49][50][51][52][53][54][55][56][57]. Table 1 The results of ♠, →, $, ♣, operations on P and Q Operations Results Table 4 The tabular form of interval-valued Pythagorean fuzzy decision matrix in Example 5.…”

Section: Discussionmentioning

confidence: 99%

New Operations for Interval-valued Pythagorean Fuzzy Set

Peng¹

2018

Scientia Iranica

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Interval-valued Pythagorean fuzzy set (IVPFS), originally proposed by Peng and Yang, is a novel tool to deal with vagueness and incertitude. As a generalized set, IVPFS has close relationship with interval-valued intuitionistic fuzzy set (IV-IFS). IVPFS can be reduced to IVIFS satisfying the condition µ + + ν + ≤ 1. However, the related operations of IVPFS do not take different conditions into consideration. In this paper, we initiate some new interval-valued Pythagorean fuzzy operators (♢, , ♠, ♣, , →, $) and discuss their properties in relation with some existing operators (∪, ∩, ⊕, ⊗) in detail. It will promote the development of interval-valued Pythagorean fuzzy operators. Later, we propose an algorithm to deal with multi-criteria decision making (MCDM) problem based on proposed ♠ operator. Finally, the effectiveness and feasibility of proposed algorithm is demonstrated by mine emergency decision making example.

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Section: Discussionmentioning

confidence: 99%

New Operations for Interval-valued Pythagorean Fuzzy Set

Peng¹

2018

Scientia Iranica

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“…For example, the idea that scores can be used to perform a regression can easily be exported to models based on hesitant fuzzy sets [11,12,[52][53][54][55] for which scores are already available [56][57][58]. It seems also feasible to export it to other hybrid soft set models (cf., Ali et al [59], Fatimah et al [60], Ma et al [16], Zhan and Zhu [14], and Zhan et al [61]). …”

Section: Discussionmentioning

confidence: 99%

Valuation Fuzzy Soft Sets: A Flexible Fuzzy Soft Set Based Decision Making Procedure for the Valuation of Assets

2017

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Zadeh's fuzzy set theory for imprecise or vague data has been followed by other successful models, inclusive of Molodtsov's soft set theory and hybrid models like fuzzy soft sets. Their success has been backed up by applications to many branches like engineering, medicine, or finance. In continuation of this effort, the purpose of this paper is to put forward a versatile methodology for the valuation of goods, particularly the assessment of real state properties. In order to reach this target, we develop the concept of (partial) valuation fuzzy soft set and introduce the novel problem of data filling in partial valuation fuzzy soft sets. The use of fuzzy soft sets allows us to quantify the qualitative attributes involved in an assessment context. As a result, we illustrate the effectiveness and validity of our valuation methodology with a real case study that uses data from the Spanish real estate market. The main contribution of this paper is the implementation of a novel methodology, which allows us to assess a large variety of assets where data are heterogeneous. Our technique permits to avoid the appraiser's subjectivity (exhibited by practitioners in housing valuation) and the well-known disadvantages of some alternative methods (such as linear multiple regression).

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“…The exploitation of soft sets and hybrid soft sets models in decision-making shows a great development in the recent years [18][19][20][21][22]. The utilization of soft rough sets models in decision-making shows a promising prospect.…”

Section: Introductionmentioning

confidence: 99%

“…The utilization of soft rough sets models in decision-making shows a promising prospect. Different decision-making approaches have been put forth based on MSR set [20], Z-soft rough fuzzy sets [17], Z-soft fuzzy rough set [21], and other soft rough sets models [23,24]. If the researchers could have a thorough knowledge of the connections among various soft rough sets, we believe that decision-making approaches under framework of soft rough sets could be applied in a more flexible and reliable way.…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study of Some Soft Rough Sets

2017

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Through the combination of different types of sets such as fuzzy sets, soft sets and rough sets, abundant hybrid models have been presented in order to take advantage of each other and handle uncertainties. A comparative study of relationships and interconnections of some existing hybrid models has been carried out. Some foundational properties of modified soft rough sets (MSR sets) are analyzed. It is pointed out that MSR approximation operators are some kinds of Pawlak approximation operators, whereas approximation operators of Z-soft rough fuzzy sets are equivalent to approximation operators of rough fuzzy sets. The relationships among F-soft rough fuzzy sets, M-soft rough fuzzy sets and Z-soft rough fuzzy sets are surveyed. A new model called soft rough soft sets has been provided as the generalization of F-soft rough sets, and its application in group decision-making has been studied. Various soft rough sets models show great potential as a tool to solve decision-making problems, and a depth study of the connections among these models contributes to the flexible application of soft rough sets based decision-making approaches.

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On a novel uncertain soft set model: Z -soft fuzzy rough set model and corresponding decision making methods

Cited by 164 publications

References 37 publications

New Operations for Interval-valued Pythagorean Fuzzy Set

New Operations for Interval-valued Pythagorean Fuzzy Set

Valuation Fuzzy Soft Sets: A Flexible Fuzzy Soft Set Based Decision Making Procedure for the Valuation of Assets

A Comparative Study of Some Soft Rough Sets

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