An Advanced Study on the Bonferroni Mean Operators for Managing Cubic Intuitionistic Complex Fuzzy Soft Settings and Their Applications in Decision Making

Mahmood, Tahir; Ali, Zeeshan; Rehman, Ubaid ur; Aslam, Muhammad

doi:10.1109/access.2022.3169862

Cited by 6 publications

(3 citation statements)

References 42 publications

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“…We can extend the HBCF framework into confidence levels BCF AOs [53]. We can use different techniques of DM like TOPSIS techniques under BCF intuitionistic fuzzy N-SSs [54]. Moreover, our idea can be extended to the following concepts of bipolar neutrosophic SSs and applications in DM [55].…”

Section: A Future Work and Limitationsmentioning

confidence: 99%

Selection of Cloud Services Provider by Utilizing Multi-Attribute Decision-Making Based on Hesitant Bipolar Complex Fuzzy Dombi Aggregation Operators

Aslam,

Waqas,

Rehman

et al. 2024

IEEE Access

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A trustworthy cloud services provider makes sure that data backups, disaster recovery, and compliance with industry standards are all met, allowing businesses to concentrate on their core competencies and innovation while leaving the complexity of IT infrastructure management to the professionals. The selection of the finest cloud services provider is a multi-attribute decision-making problem and thus, in this article, we investigate the selection of the finest cloud services provider by employing a multi-attribute decision-making technique using the invention of hesitant bipolar complex fuzzy set. The hesitant bipolar complex fuzzy sets deal not only with the data involving complex and hesitant information but also the data of dual aspects that are both positive and negative because a lot of real-life situation contains information that has hesitancy, 2 nd dimension, and a dual aspect simultaneously. Furthermore, in this manuscript, using the structure of a hesitant bipolar complex fuzzy set we initiate numerous aggregation operators. Under the environment of the proposed methodology, we invent different aggregation operators such as hesitant bipolar complex fuzzy Dombi weighted averaging, hesitant bipolar complex fuzzy Dombi ordered weighted averaging, hesitant bipolar complex fuzzy Dombi hybrid averaging, hesitant bipolar complex fuzzy Dombi weighted geometric, hesitant bipolar complex fuzzy Dombi ordered weighted geometric and hesitant bipolar complex fuzzy Dombi hybrid geometric operators. All these operators are used to solve different situations at different times. When any decision-maker wants to solve hesitation under a complex environment with 2 nd dimensions then these operators are very useful. Without proposed operators, we cannot handle the above situations because no doubt different tools for different situations are available in the market but there is no tool available for solving hesitant bipolar complex fuzzy information. Afterward, we devise a technique of multi-attribute decision-making for tackling genuine life decision-making dilemmas under the setting of hesitant bipolar complex fuzzy sets. We investigate a case study associated with cloud service providers by employing the invented technique of decision-making. In the end, we compare our newly suggested work with a few other current theories to show the effectiveness of our work. INDEX TERMSCloud services; cloud services provider; hesitant bipolar complex fuzzy set; MADM.

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Section: A Future Work and Limitationsmentioning

confidence: 99%

Selection of Cloud Services Provider by Utilizing Multi-Attribute Decision-Making Based on Hesitant Bipolar Complex Fuzzy Dombi Aggregation Operators

Aslam,

Waqas,

Rehman

et al. 2024

IEEE Access

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“…The CIFS environment gives us an effective technique to handle two-step judgement scenarios in which the lower-rank holder makes an interval-valued judgement and the upper-rank holder makes an intuitionistic fuzzy judgement during the decision-making process with the aid of the CIFS features, Garg and Kaur [26,27] examined distance measurements and the TOPSIS approach. The cubic intuitionistic complex fuzzy (CICoF) BM operator, the CICoF weighted BM operator, and their significant findings were proposed by Mahmood et al [28]. The cubic Pythagorean FS (CPyFS) [29] can be utilized as a powerful tool in an uncertain environment to solve complex decision-making problems more liberally than CIFS and IFS.…”

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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“…Wang, J [21] solved the supplier selection problem in a green supply chain by proposing a new multi-attribute decision-making approach by extending the BM operator to the 2-tuple linguistic neutrosophic number. Also, in multi-attribute decision-making, the BM operator has been extended by researchers to intuitionistic fuzzy sets [22][23][24], T-spherical fuzzy sets [25], Pythagorean fuzzy sets [26][27][28], hesitant fuzzy sets [29,30], interval fuzzy sets [31], etc., which constitutes a new aggregation operator that has achieved good results in various fields. The BM operator, compared to other FMEA methods, such as TOPSIS, ELECTRE, weighted average operator, geometric mean operator, etc., is not only able to take into account the weight relationship between risk factors, but it can also deal with the correlation between risk factors.…”

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confidence: 99%

A Novel Method for Failure Mode and Effect Analysis Based on the Fermatean Fuzzy Set and Bonferroni Mean Operator

Han,

Xia,

et al. 2024

Machines

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Failure mode and effects analysis (FMEA) helps to identify the weak points in the processing, manufacturing, and assembly of products and plays an important role in improving product reliability. To address the shortcomings of the existing FMEA methods in terms of the uncertainty treatment of information and not considering the weights and correlations between risk factors, we propose a new FMEA method. In this paper, the Fermatean fuzzy Z-number (FFZN) is proposed by fusing the Fermatean fuzzy number and Z-number. Extending it to the Bonferroni mean (BM) operator, the Fermatean fuzzy Z-number-weighted Bonferroni mean (FFZWBM) operator is proposed. A new FMEA method is proposed based on this operator. In order to overcome the factors not considered in the FMEA method, two new risk factors are proposed and added. The ability of experts to express fuzzy information is enhanced by introducing the FFS. The weights and correlations between the influencing factors can be handled by aggregating the evaluation information using the FFZWBM operator. Finally, the proposed method is applied to an arithmetic example and the accuracy of the proposed method is proved by teaming it with other methods.

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An Advanced Study on the Bonferroni Mean Operators for Managing Cubic Intuitionistic Complex Fuzzy Soft Settings and Their Applications in Decision Making

Cited by 6 publications

References 42 publications

Selection of Cloud Services Provider by Utilizing Multi-Attribute Decision-Making Based on Hesitant Bipolar Complex Fuzzy Dombi Aggregation Operators

Selection of Cloud Services Provider by Utilizing Multi-Attribute Decision-Making Based on Hesitant Bipolar Complex Fuzzy Dombi Aggregation Operators

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

A Novel Method for Failure Mode and Effect Analysis Based on the Fermatean Fuzzy Set and Bonferroni Mean Operator

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