Abstract
In order to monitor the sports load data of athletes in sports training, this paper studies the methods and systems of sports load monitoring and fatigue warning based on neural network technology. In this paper, the neural network parallel optimization algorithm based on big data is used to accurately estimate the motion load and intensity according to the determined motion mode and acceleration data, so as to realize the real-time monitoring of the exercise training. The results show that the value of η is usually small to ensure that the weight correction can truly follow the direction of the gradient descent. In this paper, 176 samples were extracted from the monitoring data collected by the “National Tennis Team Information Platform,” 160 of which were selected as training samples and the other 16 as test samples. Ant colony size M = 20. The minimum value Wmin of the weight interval is −2, and the maximum value Wmax is 2. The maximum number of iterations is set to 200. σ = 1; that is, only one optimal solution is retained. The domain is divided into 60 parts evenly; that is, r = 60. Generally, η can be taken as any number [28] between [10-3, 10], but the value is usually small to ensure that the weight correction can truly follow the direction of the gradient descent. In this paper, the value is 0.003. In the early warning stage of exercise fatigue, reasonable measurement units of exercise fatigue time were divided according to the characteristics of different exercise items. It is proved that the Bayesian classification algorithm can effectively avoid the sports injury caused by overtraining by warning the fatigue and preventing the sports injury caused by overtraining.
Highlights
Artificial neural network (ANN) is a kind of nonlinear dynamic system, which is borrowed from the development of biological neural network [1], the new intelligent information processing system
Η can be taken as any number [28] between [, 10], but the value is usually small to ensure that the weight correction can truly follow the direction of the gradient descent
In order to monitor the sports load data of athletes in sports training, this paper studies the methods and systems of sports load monitoring and fatigue warning based on neural network technology
Summary
Artificial neural network (ANN) is a kind of nonlinear dynamic system, which is borrowed from the development of biological neural network [1], the new intelligent information processing system. ACO, as a global optimization heuristic algorithm, is used to train the weight of neural network, which can avoid the defect of BP neural network. The competition of sports science and technology is increasingly fierce [3]. It is necessary to have scientific training methods and means in order to improve sports performance. Sports competition is a big competition of science and technology. Journal of Healthcare Engineering that sports training and sports science and technology are closely combined [4]. To promote the scientific sports training, give full play to the leading role of science and technology and improve the sports skills of our athletes and the competitive strength in the world competition, for our athletes in the 2008 Olympic Games to get good results to win the gold medal to make contributions [5]
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