Ansari Masfa Nasrullah, Razaq Abdul, Alolaiyan Hanan, Shuaib Umer, Salman Mohammed Abdullah, Xin Qin
Department of Mathematics, Government College University, Faisalabad, 38000, Pakistan.
Department of Mathematics, Division of Science and Technology, University of Education, Lahore, 54770, Pakistan.
Sci Rep. 2024 Oct 9;14(1):23590. doi: 10.1038/s41598-024-73488-4.
The Web 3.0 network system, the next generation of the world wide web, incorporates new technologies and algorithms to enhance accessibility, decentralization, and security, mimicking human comprehension and enabling more personalized user interactions. The key component of this environment is decentralized identity management (DIM), embracing an identity and access management strategy that empowers computing devices and individuals to manage their digital personas. Aggregation operators (AOs) are valuable techniques that facilitate combining and summarizing a finite set of imprecise data. It is imperative to employ such operators to effectively address multicriteria decision-making (MCDM) issues. Yager operators have a significant extent of adaptability in managing operational environments and exhibit excellent effectiveness in addressing decision-making (DM) uncertainties. The complex spherical fuzzy (CSF) model is more effective in capturing and reflecting the known unpredictability in a DM application. This research endeavors to enhance the DM scenario of the Web 3.0 environment using Yager aggregation operators within the CSF environment. We present two innovative aggregation operators, namely complex spherical fuzzy Yager-ordered weighted averaging (CSFYOWA) and complex spherical fuzzy Yager-ordered weighted geometric (CSFYOWG) operators. We elucidate some structural characteristics of these operators and come up with an updated score function to rectify the drawbacks of the existing score function in the CSF framework. By utilizing newly proposed operators under CSF knowledge, we develop an algorithm for MCDM problems. In addition, we adeptly employ these strategies to handle the MCDM scenario, aiming to identify the optimal approach for ensuring the privacy of digital identity or data in the evolving landscape of the Web 3.0 era. Moreover, we undertake a comparative study to highlight the veracity and proficiency of the proposed techniques compared to the previously designed approaches.
Web 3.0网络系统作为万维网的下一代，融合了新技术和算法，以提高可访问性、去中心化程度和安全性，模拟人类理解并实现更个性化的用户交互。这种环境的关键组件是去中心化身份管理（DIM），它采用一种身份和访问管理策略，使计算设备和个人能够管理自己的数字身份。聚合算子（AO）是有助于组合和汇总有限的一组不精确数据的有价值技术。必须采用此类算子来有效解决多准则决策（MCDM）问题。雅格算子在管理操作环境方面具有很大程度的适应性，并且在解决决策（DM）不确定性方面表现出出色的有效性。复杂球面模糊（CSF）模型在捕获和反映DM应用中已知的不可预测性方面更有效。本研究致力于在CSF环境中使用雅格聚合算子来增强Web 3.0环境的DM场景。我们提出了两种创新的聚合算子，即复杂球面模糊雅格有序加权平均（CSFYOWA）算子和复杂球面模糊雅格有序加权几何（CSFYOWG）算子。我们阐明了这些算子的一些结构特征，并提出了一个更新的得分函数来纠正CSF框架中现有得分函数的缺点。通过在CSF知识下使用新提出的算子，我们开发了一种用于MCDM问题的算法。此外，我们巧妙地运用这些策略来处理MCDM场景，旨在确定在Web 3.0时代不断发展的格局中确保数字身份或数据隐私的最佳方法。此外，我们进行了一项比较研究，以突出所提出技术与先前设计方法相比的准确性和熟练度。
