Psychological State and Training Method of Athletes before the Game Based on Simulated Annealing Algorithm

Abstract

The mental state of athletes before the game is the key to determining the performance of the game, and it is also the problem that every coach tries to solve. Methods: Based on this, based on the simulated annealing algorithm, the athletes' psychological state and training methods are studied before the game, and the anxiety diagnosis model and algorithm for over-training are proposed. Then the relevant data is collected, and then the Bayesian method is used to influence the psychological stress of basketball and the anxiety of different situations on the athletes' mind and body.Results:The DH algorithm is proposed, and the DH mental prediction model based on simulated annealing algorithm is constructed. The psychological modeling under the human understanding angle is predicted to try to explain the human causal model. Finally, the built model is tested and it is concluded that: the accuracy of overtraining diagnosis based on the over-trained diagnostic model and training sample data of this application example is 72.7%. When there is emotional stress, "mental exhaustion", "natural adjustment", while without "fatigue", "psychological fatigue", "feel good", "self-efficacy", "physical recovery", there is a 20.24% chance of over-training.Conclusion: Based on the psychological state of the athletes before the game, this study combines the relevant knowledge of psychology to find out the methods that affect the athletes' psychological state before the game, and provides reference for the athletes' psychological state control before the game.