Optimization of Sports Training Intensity Based on Fuzzy Control

Optimizing sports training intensity is essential for enhancing athletic performance while minimizing the risks of overtraining and injury. Traditional methods often lack the adaptability needed to accommodate an athlete’s dynamic and physiological responses. To address this, the study introduces the Fuzzy Control-based Training Optimization Framework (FC-TOF), an intelligent and adaptive approach to managing training intensity. The FC-TOF integrates fuzzy control techniques with real time physiological data, such as heart rate variability, perceived exertion, and training volume. These inputs are processed through a fuzzy logic system to provide personalized, dynamic training intensity adjustments based on individual performance goals and physical conditions. The FC-TOF has been validated using historical athlete data and tested on participants from various sports disciplines. The implementation of FC-TOF exhibited significant enhancements in training results. Athletes exhibited increased endurance, superior peak performance measures, reduced injury rates, and more effective recovery management than traditional techniques. The technology promoted improved adherence to training schedules by offering personalized, data-informed recommendations. This study highlights the efficacy of FC-TOF as a useful tool for improving sports training intensity. The study provides a dependable basis for personalized training methodologies, improving athletic performance while mitigating training-related hazards.

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Publication Details

Journal
International Journal of Computational Intelligence Systems
Published
2026-02-01
DOI
https://doi.org/10.1007/s44196-026-01158-6
Primary Topic
Sports Performance and Training
Type
article
Field-Weighted Citation Impact
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article

Optimization of Sports Training Intensity Based on Fuzzy Control

Mingbao Yan, Ying Sun, Mingjin Yan, Xun Cui
International Journal of Computational Intelligence Systems
Sports Performance and Training
article

Optimization of Sports Training Intensity Based on Fuzzy Control

Mingbao Yan, Ying Sun, Mingjin Yan, Xun Cui
article en

Abstract

Optimizing sports training intensity is essential for enhancing athletic performance while minimizing the risks of overtraining and injury. Traditional methods often lack the adaptability needed to accommodate an athlete’s dynamic and physiological responses. To address this, the study introduces the Fuzzy Control-based Training Optimization Framework (FC-TOF), an intelligent and adaptive approach to managing training intensity. The FC-TOF integrates fuzzy control techniques with real time physiological data, such as heart rate variability, perceived exertion, and training volume. These inputs are processed through a fuzzy logic system to provide personalized, dynamic training intensity adjustments based on individual performance goals and physical conditions. The FC-TOF has been validated using historical athlete data and tested on participants from various sports disciplines. The implementation of FC-TOF exhibited significant enhancements in training results. Athletes exhibited increased endurance, superior peak performance measures, reduced injury rates, and more effective recovery management than traditional techniques. The technology promoted improved adherence to training schedules by offering personalized, data-informed recommendations. This study highlights the efficacy of FC-TOF as a useful tool for improving sports training intensity. The study provides a dependable basis for personalized training methodologies, improving athletic performance while mitigating training-related hazards.

International Journal of Computational Intelligence SystemsVol. 19(1)
Qingdao University (CN), Heilongjiang Vocational College of Art (CN), Myongji University (KR)
Openalex Percentile: Top 72%
Sports Performance and Training
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