Hussain Abrar, Ullah Kifayat, Senapati Tapan, Moslem Sarbast
Department of Mathematics, Riphah International University Lahore, Lahore Campus, 5400, Lahore, Pakistan.
School of Mathematics and Statistics, Southwest University, Chongqing, People's Republic of China.
Heliyon. 2023 Jul 7;9(7):e18100. doi: 10.1016/j.heliyon.2023.e18100. eCollection 2023 Jul.
The multi-criteria decision-making (MCDM) tool is a robust decision-making technique utilized in several fields like networking, risk management, digital analysis, cybercrime investigation, artificial intelligence, waste management enterprises and many other selection criteria. Complex SFS (CSFS) is a new edition of the spherical fuzzy set (SFS) that offers substantial information about any item in terms of amplitude and phase terms in a wider range of real terms. Complex SFS (CSFS) can be an extension of the spherical fuzzy set (SFS). The Aczel-Alsina aggregation tools are more appropriate aggregation operators (AOs), and they are used to conquer the impact of inconsistent and uncertain data. In this paper, we reveal some new approaches based on Aczel-Alsina aggregation tools under consideration of Complex Spherical Fuzzy (CSF) information. These new approaches include the CSF Aczel-Alsina weighted average (CSFAWA) operator, and the CSF Aczel-Alsina ordered weighted average (CSFOWA) operator. In addition to this, we also introduce a list of novel techniques by making use of the theory of Aczel-Alsina aggregation tools such as CSF Aczel-Alsina weighted geometric (CSFAWG) and CSF Aczel-Alsina ordered weighted geometric (CSFOWG) operators. To demonstrate the resilience and efficacy of the approaches that have been mentioned, we will examine a few exceptional examples and remarkable properties of the methodology that we have devised. In addition, a characterization is provided for an approach to the MCDM issue using the CPF information system. We use the example of electric automobiles as a case study to illustrate the uniformity and dependability of the methodology that we have established. This example was chosen because of the high cost of fuel and the present economic challenges that are being encountered by families in the middle class. An empirical case study is also constructed to determine an electric car that is desirable based on the techniques that we have proposed. To evaluate the correctness and superiority of the established strategies, we compare the outcomes of previously used techniques with the AOs currently being provided.
多准则决策（MCDM）工具是一种强大的决策技术，应用于多个领域，如网络、风险管理、数字分析、网络犯罪调查、人工智能、废物管理企业以及许多其他选择标准。复杂球面模糊集（CSFS）是球面模糊集（SFS）的新版本，它在更广泛的实际意义上，从幅度和相位方面提供了关于任何项目的大量信息。复杂球面模糊集（CSFS）可以是球面模糊集（SFS）的扩展。阿泽尔 - 阿尔西纳聚合工具是更合适的聚合算子（AO），它们用于克服不一致和不确定数据的影响。在本文中，我们揭示了一些基于阿泽尔 - 阿尔西纳聚合工具并考虑复杂球面模糊（CSF）信息的新方法。这些新方法包括CSF阿泽尔 - 阿尔西纳加权平均（CSFAWA）算子和CSF阿泽尔 - 阿尔西纳有序加权平均（CSFOWA）算子。除此之外，我们还利用阿泽尔 - 阿尔西纳聚合工具理论引入了一系列新技术，如CSF阿泽尔 - 阿尔西纳加权几何（CSFAWG）和CSF阿泽尔 - 阿尔西纳有序加权几何（CSFOWG）算子。为了证明所提及方法的弹性和有效性，我们将研究一些特殊示例以及我们所设计方法的显著特性。此外，还提供了一种使用CPF信息系统解决MCDM问题的方法的特征描述。我们以电动汽车为例进行案例研究，以说明我们所建立方法的一致性和可靠性。选择这个例子是因为燃料成本高昂以及中产阶级家庭目前面临的经济挑战。还构建了一个实证案例研究，以根据我们提出的技术确定一辆理想的电动汽车。为了评估既定策略的正确性和优越性，我们将先前使用的技术结果与当前提供的AO进行比较。
