2020
DOI: 10.1155/2020/8868225
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Performance Optimization Mechanism of Adolescent Physical Training Based on Reinforcement Learning and Markov Model

Abstract: Upon the teenagers’ failure to obtain the plenty of physical exercises at the growth and development stage, the related central nervous system is prone to degeneration and the physical fitness starts to decline gradually. In fact, through monitoring the exercise process real-timely and quantifying the exercise data, the adolescent physical training can be effectively conducted. For such process, it involves two issues, i.e., the real-time data monitoring and data quantification evaluation. Therefore, this pape… Show more

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Cited by 3 publications
(1 citation statement)
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“…Aiming at the monitoring and quantitative evaluation of data, we put forward a monitoring and evaluation method of sports training effect based on reinforcement learning (RL) and the Markov model. Compared with the traditional monitoring mechanism, this method can train them more efficiently, and the deviation rate of evaluation is very low [ 8 ]. By combining 5G and the Internet of Things, our proposed system can be used to detect the physical health information of teenagers in real time, and, according to the quantified health level and exercise amount, it can achieve the purpose of monitoring teenagers' physical health [ 8 ].…”
Section: Introductionmentioning
confidence: 99%
“…Aiming at the monitoring and quantitative evaluation of data, we put forward a monitoring and evaluation method of sports training effect based on reinforcement learning (RL) and the Markov model. Compared with the traditional monitoring mechanism, this method can train them more efficiently, and the deviation rate of evaluation is very low [ 8 ]. By combining 5G and the Internet of Things, our proposed system can be used to detect the physical health information of teenagers in real time, and, according to the quantified health level and exercise amount, it can achieve the purpose of monitoring teenagers' physical health [ 8 ].…”
Section: Introductionmentioning
confidence: 99%