A Novel Multi-attribute Group Decision-Making Method Based on Interval-Valued q-rung Dual Hesitant Fuzzy Sets and TOPSIS

Wang, Jun; Xu, Wuhuan; Xu, Yan; Li, Li; Feng, Xue

doi:10.1007/978-981-16-8656-6_23

Cited by 4 publications

(2 citation statements)

References 12 publications

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“…It should be noted that IVq-ROFSs significantly reduce to q-ROFSs, indicating that the latter is a particular case of the former, where both the upper and lower boundaries of the interval values are equal. As a result, Wang et al [16] published a novel solution strategy for interval-valued q-rung dual hesitant fuzzy MAGDM problems. However, features of many activities in the current world cannot be evaluated quantitatively rather, they must be evaluated qualitatively, i.e., using imprecise information.…”

Section: Introductionmentioning

confidence: 99%

MAGDM for selecting machine learning techniques: A novel approach utilizing the 2-tuple linguistic cubic q-rung orthopair fuzzy set

Naz

Akram

Sagheer

et al. 2023

Preprint

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Machine learning is a powerful technology for both current and future information management and it is already being used in a variety of domains. The use of machine learning in cyber security is still in its early stages, emphasizing the significant gap between research and practice. The q-rung orthopair fuzzy set (q-ROFS) has been demonstrated to be a valuable tool in describing decision-makers (DMs) assessment values in multi-attribute group decision-making (MAGDM). In this paper, we introduce a new tool called the 2-tuple linguistic cubic q-rung orthopair fuzzy set (2TLCq-ROFS) based on the combination of q-ROFS with interval-valued q-ROFS under the 2-tuple linguistic scenario in order to capture DMs assessment information in the complex MAGDM problems in a more efficient way. We investigate machine learning based MAGDM problems in cyber security in which the DM’s preference information is expressed as the 2TLCq-ROF numbers (2TLCqROFNs). Based on the combination of power average and power geometric operators with Muirhead mean, we propose a family of new aggregation operators including: the 2TLCq-ROF power Muirhead mean (2TLCq-ROFPMM), the 2TLCq-ROF dual power Muirhead mean (2TLCq-ROFDPMM), the 2TLCq-ROF weighted power Muirhead mean (2TLCq-ROFWPMM), and the 2TLCq-ROF weighted dual power Muirhead mean (2TLCq-ROFWDPMM) operators under the 2TLCq-ROF environment, which are more precise than the current aggregation operators and take into account the interconnection of the 2TLCq-ROFNs. Then, a versatile 2TLCq-ROF MAGDM approach is established and a case study on the evaluation of machine learning techniques in cyber security is given to show the method’s effectiveness and validity. Moreover, a parameter analysis is carried out to analyze the influence of parameters on ranking results. The comparative analysis further confirms the effectiveness and feasibility of the proposed approach to show why DMs should select our suggested strategy over several others. In the end, some conclusions of this paper are determined and future directions are demonstrated.

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Section: Introductionmentioning

confidence: 99%

MAGDM for selecting machine learning techniques: A novel approach utilizing the 2-tuple linguistic cubic q-rung orthopair fuzzy set

Naz

Akram

Sagheer

et al. 2023

Preprint

View full text Add to dashboard Cite

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“…Garg et al [18] proposed a new TOPSIS method based on the complex interval-valued q-rung orthopair fuzzy set. Wang et al [19] have introduced a TOPSIS method for interval-valued q-rung dual hesitant fuzzy sets. Huang et al [20] have presented aggregation operators for spherical fuzzy rough sets (SFR), and they have used them to propose a new TOPSIS algorithm in spherical fuzzy rough environment.…”

Section: Introductionmentioning

confidence: 99%

Single and Interval-Valued Hybrid Enthalpy Fuzzy Sets and a TOPSIS Approach for Multicriteria Group Decision Making

Olgun

Türkarslan

et al. 2022

Mathematical Problems in Engineering

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The concept of entropy is one of the most important notions of the information theory. Entropy quantifies the amount of uncertainty involved in the value of a random variable or the outcome of a random process. Shannon’s entropy is one of the most useful entropy types. The notion of enthalpy is the information energy expressed by the complement of Shannon’s entropy. In this paper, we propose the concept of interval-valued hybrid enthalpy fuzzy set by modifying single and interval-valued fuzzy multisets. In this context, an interval-valued hybrid enthalpy fuzzy set contains information about both the data and their entropy. We also provide a cosine similarity measure between interval-valued hybrid enthalpy fuzzy sets. Using this cosine similarity measure, we propose a TOPSIS approach for multicriteria group decision making. Moreover, we apply the proposed TOPSIS method to a research assistant selection problem, and we compare the result with the result of a classical TOPSIS method.

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Information Measures for Continuous Function-Valued q-Rung Orthopair Fuzzy Sets and an Extended TOPSIS

Ünver,

Aydoğan

2024

J. Uncert. Sys.

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The concept of continuous function-valued [Formula: see text]-rung orthopair fuzzy set (CFV[Formula: see text]ROFS) represents an innovative framework within fuzzy set theory, where the assessment of an element’s membership and nonmembership degrees is accomplished through continuous functions. This paper introduces a novel entropy measure for CFV[Formula: see text]ROFS, employing the Riemann integral. Furthermore, it outlines a theoretical framework for constructing a similarity measure based on entropy and presents a distance measure. The newly introduced entropy measure is used for weighting criteria and measuring the distance of the alternatives in decision-making processes. To illustrate the practical utility of these concepts, an extended Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is proposed and is employed to tackle a real-world problem previously addressed in the literature. The outcomes of this extended TOPSIS are compared with those given in existing studies, and a sensitivity analysis is performed concerning the variable [Formula: see text].

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A Novel Multi-attribute Group Decision-Making Method Based on Interval-Valued q-rung Dual Hesitant Fuzzy Sets and TOPSIS

Cited by 4 publications

References 12 publications

MAGDM for selecting machine learning techniques: A novel approach utilizing the 2-tuple linguistic cubic q-rung orthopair fuzzy set

MAGDM for selecting machine learning techniques: A novel approach utilizing the 2-tuple linguistic cubic q-rung orthopair fuzzy set

Single and Interval-Valued Hybrid Enthalpy Fuzzy Sets and a TOPSIS Approach for Multicriteria Group Decision Making

Information Measures for Continuous Function-Valued q-Rung Orthopair Fuzzy Sets and an Extended TOPSIS

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