Comprehensive Analysis Using 2-tuple Linguistic Neutrosophic MADM with Core Competencies Evaluation of Track and Field Students in Sports Colleges

Abstract

The core competencies evaluation of track and field students in sports colleges holds 
significant importance. It not only helps assess students' overall abilities in track and field, such as 
physical fitness, athletic skills, psychological quality, and social responsibility, but also provides a 
scientific basis for personalized teaching and training. Through this evaluation, students' strengths 
and weaknesses can be identified, allowing for the optimization of training strategies to improve 
their athletic performance and holistic development. Additionally, this evaluation aids in cultivating 
students' teamwork, psychological resilience, and sense of social responsibility, ensuring that they 
are more competitive and adaptable in their future sports careers, thereby promoting their long-term 
development. The core competencies evaluation of track and field students in sports colleges is 
regarded as a multi-attribute decision-making (MADM) problem. In this study, we integrated the 
geometric Heronian mean (GHM) approach and prioritized aggregation (PA) with 2-tuple linguistic 
neutrosophic numbers (2TLNNs) to develop the generalized 2-tuple linguistic neutrosophic 
numbers prioritized GHM (G2TLNPGHM) approach. Additionally, we explored several key 
properties of the proposed approach. The G2TLNPGHM approach was then applied to address 
MADM problems under the framework of 2TLNNs. To demonstrate its practical application, the 
method was used as an example for evaluating the core competencies of track and field students in 
sports colleges. Lastly, a comprehensive comparative analysis was conducted to examine the effects 
of varying parameters on the results. 

DOI: 10.5281/zenodo.14121422