Achievement Prediction and Performance Assessment System for Nations in the Asian Games

Author:

Yeh Chin-Chang12,Peng Hsien-Te3ORCID,Lin Wen-Bin4ORCID

Affiliation:

1. School of Dance, Taipei National University of the Arts, Taipei City 11201, Taiwan

2. Graduate Institute of Sport Coaching Science, Chinese Culture University, Taipei City 11114, Taiwan

3. Department of Physical Education, Chinese Culture University, Taipei City 11114, Taiwan

4. Physical Education Center, Taipei National University of the Arts, No. 1, Hsueh-Yuan Road, Peitou, Taipei City 11201, Taiwan

Abstract

The profound impact of deep learning technology is poised to revolutionize various industries, marking the fourth industrial revolution. Thus, we combined efficiency and productivity research (data envelopment analysis, DEA), artificial intelligence and deep learning (artificial neural networks, ANN), a system integrating DEA and ANNs, and simultaneous longitudinal research (time series) to determine comprehensive research trends and create relevant applications. We addressed mega-sports events’ performance assessment systems that predict the efficiency of nations participating in the Asian Games from 1990 to 2023 and analyzed the outcomes, applying them to practical issues of national sports policies and development. Performance assessment systems to diagnose, plan, monitor, and revise the impact of implementing measures in Asian nations represent a step forward. The PAS findings point out future research recommendations by addressing national sports policies and development issues, transforming the predictions of performance assessment systems in mega-sports events into practical management recommendations. In this way, the system for enhanced predictive analytics developed in the study can rapidly analyze large, medium, and small datasets, reveal insights that humans may overlook, and refine the likelihood of predicting future events with greater precision and accuracy.

Funder

Ministry of Science and Technology of Taiwan

Publisher

MDPI AG

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