Department of Mathematics, College of Science & Arts, King Abdulaziz University, Rabigh, Saudi Arabia.
Division of Science and Technology, Department of Mathematics, University of Education, Lahore, Pakistan.
PLoS One. 2024 Aug 23;19(8):e0307381. doi: 10.1371/journal.pone.0307381. eCollection 2024.
Big data pertains to extensive and intricate compilations of information that necessitate the implementation of proficient and cost-effective evaluation and analysis tools to derive insights and support decision making. The Fermatean fuzzy set theory possesses remarkable capability in capturing imprecision due to its capacity to accommodate complex and ambiguous problem descriptions. This paper presents the study of the concepts of dynamic ordered weighted aggregation operators in the context of Fermatean fuzzy environment. In numerous practical decision making scenarios, the term "dynamic" frequently denotes the capability of obtaining decision-relevant data at various time intervals. In this study, we introduce two novel aggregation operators: Fermatean fuzzy dynamic ordered weighted averaging and geometric operators. We investigate the attributes of these operators in detail, offering a comprehensive description of their salient features. We present a step-by-step mathematical algorithm for decision making scenarios in the context of proposed methodologies. In addition, we highlight the significance of these approaches by presenting the solution to the decision making problem and determining the most effective big data analytics platform for YouTube data analysis. Finally, we perform a thorough comparative analysis to assess the effectiveness of the suggested approaches in comparison to a variety of existing techniques.
大数据涉及广泛而复杂的信息集合，需要实施高效且具有成本效益的评估和分析工具，以从中获取洞察并支持决策制定。由于能够处理复杂和模糊的问题描述，Fermatean 模糊集理论在捕捉不精确性方面具有显著的能力。本文研究了 Fermatean 模糊环境下的动态有序加权聚合算子的概念。在许多实际决策场景中，术语“动态”通常表示在不同时间间隔获取与决策相关的数据的能力。在这项研究中，我们引入了两种新的聚合算子：Fermatean 模糊动态有序加权平均和几何算子。我们详细研究了这些算子的属性，全面描述了它们的显著特征。我们提出了一个用于提出的方法背景下的决策场景的逐步数学算法。此外，我们通过提出决策问题的解决方案并确定最有效的 YouTube 数据分析大数据分析平台来强调这些方法的重要性。最后，我们进行了全面的比较分析，以评估与各种现有技术相比，所提出方法的有效性。
