Digital technology implementation and impact of artificial intelligence based on bipolar complex fuzzy Schweizer–Sklar power aggregation operators

Mahmood, Tahir; Rehman, Ubaid ur

doi:10.1016/j.asoc.2023.110375

Cited by 7 publications

(3 citation statements)

References 67 publications

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“…Schweizer and Sklar ( 2011 ) invented the SS operator. Mahmood and ur Rehman ( 2023 ) investigated the principles for operation depend on the t-norm and t-conorm of SS and created aggregation operators based on these operational laws in the context of a Bipolar complex fuzzy BCF collection. Chen et al ( 2023 ) proposed an advanced method for multi-attribute decision-making (MADM) in the context of q -rung orthopair probabilistic hesitant fuzzy environments.…”

Section: Introductionmentioning

confidence: 99%

A MAGDM approach for evaluating the impact of artificial intelligence on education using 2-tuple linguistic q-rung orthopair fuzzy sets and Schweizer-Sklar weighted power average operator

Mahboob,

Ullah,

Ovais

et al. 2024

Front. Artif. Intell.

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The impact of artificial intelligence (AI) in education can be viewed as a multi-attribute group decision-making (MAGDM) problem, in which several stakeholders evaluate the advantages and disadvantages of AI applications in educational settings according to distinct preferences and criteria. A MAGDM framework can assist in providing transparent and logical recommendations for implementing AI in education by methodically analyzing the trade-offs and conflicts among many components, including ethical, social, pedagogical, and technical concerns. A novel development in fuzzy set theory is the 2-tuple linguistic q-rung orthopair fuzzy set (2TLq-ROFS), which is not only a generalized form but also can integrate decision-makers quantitative evaluation ideas and qualitative evaluation information. The 2TLq-ROF Schweizer-Sklar weighted power average operator (2TLq-ROFSSWPA) and the 2TLq-ROF Schweizer-Sklar weighted power geometric (2TLq-ROFSSWPG) operator are two of the aggregation operators we create in this article. We also investigate some of the unique instances and features of the proposed operators. Next, a new Entropy model is built based on 2TLq-ROFS, which may exploit the preferences of the decision-makers to obtain the ideal objective weights for attributes. Next, we extend the VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) technique to the 2TLq-ROF version, which provides decision-makers with a greater space to represent their decisions, while also accounting for the uncertainty inherent in human cognition. Finally, a case study of how artificial intelligence has impacted education is given to show the applicability and value of the established methodology. A comparative study is carried out to examine the benefits and improvements of the developed approach.

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Section: Introductionmentioning

confidence: 99%

A MAGDM approach for evaluating the impact of artificial intelligence on education using 2-tuple linguistic q-rung orthopair fuzzy sets and Schweizer-Sklar weighted power average operator

Mahboob,

Ullah,

Ovais

et al. 2024

Front. Artif. Intell.

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“…The Aczel-Alsina AOs and Maclaurin symmetric mean operators in the setting of BCF set were discussed by Mahmood et al [38] and Mahmood and Rehman [39]. The digital technology implementation under the setting of BCFS was devised by Mahmood and Rehman [40]. It is possible to obtain comparably accurate estimates by using logarithmic operations, which are frequently disregarded in favor of algebraic operations.…”

Section: Introductionmentioning

confidence: 99%

Selection of Software Development Methodology by Employing a Multi-Criteria Decision-Making Approach Based on Logarithmic Bipolar Complex Fuzzy Aggregation Operators

Song,

Mahmood,

Rehman

2024

IEEE Access

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Numerous factors, including project complexity, team size, customer collaboration, and development pace, must be taken into consideration while choosing a software development methodology. This problem is a multi-criteria decision-making dilemma since the many criteria frequently fight with one another and fluctuate in priority. To systematically select the best methodology, the multi-criteria decisionmaking technique assists in quantifying and assessing these factors. This ensures that decisions are made in a fair and informed manner within the context of the challenging software development environment. Thus, in this article, we develop a multi-criteria decision-making approach in the setting of bipolar complex fuzzy information for the prioritization and selection of optimal software development methodology. For this, we first, invent logarithmic operational laws and associated results for the bipolar complex fuzzy set. Then, we invent four aggregation operators by utilizing these logarithmic operational laws under the structure of bipolar complex fuzzy information, that is, logarithmic bipolar complex fuzzy weighted averaging, logarithmic bipolar complex fuzzy ordered weighted averaging, logarithmic bipolar complex fuzzy weighted geometric, and logarithmic bipolar complex fuzzy ordered weighted geometric. After that, we solve a multi-criteria decision-making dilemma related to the prioritization and selection of software development methodology by considering the artificial data in the setting of bipolar complex fuzzy information and achieve that "Agile" is the optimal software development methodology among the considered four different software development methodologies, i.e., Waterfall, DevOps, Spiral, and Agile. In the last, we investigate the comparison study of the deduced theory to a few current theories to reveal the importance and supremacy of the constructed theory.INDEX TERMS Software development methodology; logarithmic operations; bipolar complex fuzzy set; MCDM.

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“…To handle such type of information the idea of a Bipolar complex fuzzy set (BCFS) was given by Mahmood and Rehman [43] with the title A Novel Approach towards BCFSs and their use in generic similarity metrics. Mahmood and Rehman [44] also proposed the Artificial intelligence deployment in digital technology and its effects based on BCF Schweizer-Sklar power AOs. Additionally, Xu et al [45] explored the use of the MADM technique based on the BCF Dombi Prioritized AOs to analyze structural systems to design earthquake-resistant structures.…”

Section: Introductionmentioning

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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Digital technology implementation and impact of artificial intelligence based on bipolar complex fuzzy Schweizer–Sklar power aggregation operators

Cited by 7 publications

References 67 publications

A MAGDM approach for evaluating the impact of artificial intelligence on education using 2-tuple linguistic q-rung orthopair fuzzy sets and Schweizer-Sklar weighted power average operator

A MAGDM approach for evaluating the impact of artificial intelligence on education using 2-tuple linguistic q-rung orthopair fuzzy sets and Schweizer-Sklar weighted power average operator

Selection of Software Development Methodology by Employing a Multi-Criteria Decision-Making Approach Based on Logarithmic Bipolar Complex Fuzzy Aggregation Operators

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

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