Activity Classification and Analysis During a Sports Training Session Using a Fuzzy Model
Training has great significance and should be an integral part of the daily routines of all elite athletes. Training allows the body to gradually develop strength and endurance, increase skill levels, and build trust, motivation, and ambition. The risk factors in sports training sessions include fragile or low self-confidence, Breakdowns in self-assurance, and high expectations are considered an important factors. In this paper, Dynamic Activity Adaptive Physical Fuzzy Model (DAAPFM) is proposed to become better athletes and meet their mental challenges. Mel does time-frequency analysis, and they tend to experience anxiety about performance. Fuzzy wrapping optimization analysis is integrated with DAAPFM to build confidence in the belief in one's ability to execute a task or win an event. The experimental results show that the data fusion approach can analyze the activities of athletes effectively. The simulation results give the average accuracy of the classification of sports activity 99.40% framework's efficiency to gradually develop strength and endurance, increase skill levels, and build trust, motivation, and ambition.
International Journal on Artificial Intelligence Tools
Huang, Xianfeng; Li, Hui; Zhou, Hu; Krishnamoorthy, Sujatha; and Kadry, Seifedine Nimer, "Activity Classification and Analysis During a Sports Training Session Using a Fuzzy Model" (2022). Kean Publications. 570.