APPLICATION ANALYSIS OF DIGITAL NEURAL NETWORK-BASED DATA MINING METHOD IN MAXIMIZING THE PERFORMANCE OF SPORTS TRAINING
ABSTRACT Introduction: In today's rapid development of science and technology, digital network data mining technology is developing as fast as the expansion of the frontiers of science and technology allows, with a very broad application level, covering most of the civilized environment. However, there is still much to explore in the application of sports training. Objective: Analyze the feasibility of data mining based on the digital network of sports training, maximizing athletes’ training. Methods: This paper uses the experimental analysis of human FFT, combined with BP artificial intelligence network and deep data mining technology, to design a new sports training environment. The controlled test of this model was designed to compare advanced athletic training modalities with traditional modalities, comparing the athletes’ explosive power, endurance, and fitness. Results: After 30 days of physical training, the athletic strength of athletes with advanced fitness increased by 15.33%, endurance increased by 15.85%, and fitness increased by 14.23%. Conclusion: The algorithm designed in this paper positively impacts maximizing athletes’ training. It may have a favorable impact on training outcomes, as well as increase the athlete's interest in the sport. Level of evidence II; Therapeutic studies - investigating treatment outcomes.
| Main Authors: | , , , , |
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| Format: | Digital revista |
| Language: | English |
| Published: |
Sociedade Brasileira de Medicina do Exercício e do Esporte
2023
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| Online Access: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1517-86922023000100344 |
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