Interval-Valued Picture Fuzzy Maclaurin Symmetric Mean Operator with application in Multiple Attribute Decision-Making

Ashraf, Ansa; Ullah, Kifayat; Hussain, Amir; Bari, Mehwish

doi:10.31181/rme20020042022a

Cited by 110 publications

(48 citation statements)

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“…Ali et al [15] used complex interval-valued Pythagorean fuzzy set in green supplier chain management. Ashraf et al [16] introduced interval-valued picture fuzzy Maclaurin symmetric mean operator as application in decision-making problem. In the instance of q-rung orthopair fuzzy set (q-ROFS) [17][18][19], the conditions on membership function and non-membership functions are changed to 0 ≤ u q + v q ≤ 1(q ≥ 1).…”

Section: Introductionmentioning

confidence: 99%

Analysis of Cryptocurrency Market by Using q‐Rung Orthopair Fuzzy Hypersoft Set Algorithm Based on Aggregation Operators

et al. 2022

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One of the most important innovations brought by digitization is the cryptocurrency, also called virtual or digital currency, which has been discussed in recent years and in particular is a new platform for investors. Different types of cryptocurrencies such as Bitcoin, Ethereum, Binance Coin, and Tether do not depend on a central authority. Decision making is complicated by categorization and transmission of uncertainty, as well as verification of digital currency. The weighted average and weighted geometric aggregation operators are used in this article to define a multi-attribute decision-making approach. This work investigates the uniqueness of q-rung orthopair fuzzy hypersoft sets (q-ROFHSS), which respond to instabilities, uncertainty, ambiguity, and imprecise information. This research also covers some fundamental topics of q-ROFHSS. The model offered here is the best option for learning about electronic currency. This study validates the complexity of decision-making problems with different attributes and subattributes to obtain an optimal choice. We conclude that Bitcoin has a diverse set of applications and that crypto assets are well positioned to become an important asset class in decision making.

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Section: Introductionmentioning

confidence: 99%

Analysis of Cryptocurrency Market by Using q‐Rung Orthopair Fuzzy Hypersoft Set Algorithm Based on Aggregation Operators

et al. 2022

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“…These methods are valuable and address the main challenges of MCDA techniques such as rank reversal paradox resistance or handling uncertainty. Sometimes, authors propose a new operators to support decision making [ 40 , 41 , 42 ].…”

Section: Introductionmentioning

confidence: 99%

Making Group Decisions within the Framework of a Probabilistic Hesitant Fuzzy Linear Regression Model

Sultan

Sałabun

Faizi

et al. 2022

Sensors

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A fuzzy set extension known as the hesitant fuzzy set (HFS) has increased in popularity for decision making in recent years, especially when experts have had trouble evaluating several alternatives by employing a single value for assessment when working in a fuzzy environment. However, it has a significant problem in its uses, i.e., considerable data loss. The probabilistic hesitant fuzzy set (PHFS) has been proposed to improve the HFS. It provides probability values to the HFS and has the ability to retain more information than the HFS. Previously, fuzzy regression models such as the fuzzy linear regression model (FLRM) and hesitant fuzzy linear regression model were used for decision making; however, these models do not provide information about the distribution. To address this issue, we proposed a probabilistic hesitant fuzzy linear regression model (PHFLRM) that incorporates distribution information to account for multi-criteria decision-making (MCDM) problems. The PHFLRM observes the input–output (IPOP) variables as probabilistic hesitant fuzzy elements (PHFEs) and uses a linear programming model (LPM) to estimate the parameters. A case study is used to illustrate the proposed methodology. Additionally, an MCDM technique called the technique for order preference by similarity to ideal solution (TOPSIS) is employed to compare the PHFLRM findings with those obtained using TOPSIS. Lastly, Spearman’s rank correlation test assesses the statistical significance of two rankings sets.

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“…Some useful investigations (Wang and Liu 2011 ; Ali et al 2021 ; Garg 2016b , 2017b ) have been conducted using Einstein t-norm operations under different fuzzy frameworks. Several pieces of research (Ashraf et al 2022 ; Liu and Wang 2018 ; Sahu et al 2021 ; Limboo and Dutta 2022 ; Kazimieras Zavadskas et al 2020 ; Karamaşa et al 2021 ; Yager 2013b ) have played their part to remove the obscurities during the process of MAGDM or MADM under IFSs, PyFSs, and q-ROFSs. Besides it, some researchers made valuable contributions to enhancing the scope of MADM problems under different fuzzy environments (Wang and Triantaphyllou 2008 ; Arora and Garg 2019 , 2018 ; Xu and Hu 2010 ; Xu 1988 , 2005 ; Viriyasitavat 2016 ; Kaur and Garg 2018 ).…”

Section: Introductionmentioning

confidence: 99%

Approach to multi-attribute decision-making problems based on neutrality aggregation operators of T-spherical fuzzy information

et al. 2022

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In the process of decision-making , uncertain information is always challenging to deal with. T-spherical fuzzy set (TSFS) operates vagueness of data by analysing three independent functions, namely membership, non-membership, and abstinence function. The TSFS provides us robust scheme with parameter to handle the countless opportunities. Hence, this set proves its superiority over the existing picture fuzzy set (PFS) and spherical fuzzy set (SFS). Now a day, decision-makers usually assign impartial values throughout the assessment. This manuscript demonstrates some new operational laws by fusing the neutral characteristics of the degrees of membership and using the probability sum (PS) function. Meanwhile, we determine several aggregation operators (AOs) including weighted averaging neutral, ordered weighed neutral, and hybrid averaging neutral AOs to aggregate the data under T-spherical fuzzy (TSF) environment. As it came to the notice that weighted neutral averaging aggregation operators of the Pythagorean fuzzy set (PyFS), single-valued neutrosophic fuzzy set (SVNFS), and -rung orthopair fuzzy set ( -ROFS) have some restrictions during the decision-making problems. So, to overcome this, we introduce a new multi-attribute group decision-making method (MAGDM) based on proposed AOs. Lastly, we provide various numerical instances to explain the method and exhibit its supremacy. Furthermore, a comparative analysis is conducted to compare the potential of proposed AOs with some other existing methods.

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Interval-Valued Picture Fuzzy Maclaurin Symmetric Mean Operator with application in Multiple Attribute Decision-Making

Cited by 110 publications

References 0 publications

Analysis of Cryptocurrency Market by Using q‐Rung Orthopair Fuzzy Hypersoft Set Algorithm Based on Aggregation Operators

Analysis of Cryptocurrency Market by Using q‐Rung Orthopair Fuzzy Hypersoft Set Algorithm Based on Aggregation Operators

Making Group Decisions within the Framework of a Probabilistic Hesitant Fuzzy Linear Regression Model

Approach to multi-attribute decision-making problems based on neutrality aggregation operators of T-spherical fuzzy information

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