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WASPAS-based multi-expert decision algorithm for physical education using circular pythagorean fuzzy aggregation with
Dawei Lyu1, Xiaoxue Zhang2,3
1College of Physical Education and Health, East China Jiaotong University, Nan Chang, 330013, Jiangxi, China. lvdawei13330116957@163.com.
Abstract:
Decision-making is a crucial process that involves selecting a course of action from multiple alternatives. It requires evaluating different options, weighing their potential outcomes, and making a choice based on available information and objectives. In physical education, decision-making plays a vital role in instructing teachers and students to interact with each other, facilitating understanding and retention of previously learned material. In this article discusses decision-making in physical education for teaching and learning, aiming to create engaging and inspiring opportunities for students to learn and improve their thinking skills. To achieve this, we utilize a circular Pythagorean fuzzy set (CPyFS), which captures membership and non-membership grades while exhibiting circular behavior. This approach is particularly useful for handling uncertainty in assessment processes, allowing decision-makers ([Formula: see text]) to discuss their opinions within a large domain. The CPyFS technique builds upon fuzzy set (FS) theory, with Pythagorean FS (PyFS) being a special case. Our goal is to define weighted averaging and geometric operators within the CPyFS framework, based on triangular norms. We demonstrate the effectiveness of these aggregation operators (AOs) through examples and establish key mathematical properties, such as idempotency and boundedness. Furthermore, we propose a new model using the weighted aggregated sum product assessment (WASPAS) method, exploring its application in multi-criteria group decision-making (MCGDM). The effectiveness and reliability of this technique are validated through sensitivity analysis and comparative study, showcasing its potential in handling uncertainties in physical education.
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