RESEARCH ON ATHLETES’ PSYCHOLOGICAL REGULATION ABILITY BASED ON BACK PROPAGATION (BP) NEURAL NETWORK ALGORITHM

INVESTIGAÇÃO SOBRE A HABILIDADE DE CONTROLE PSICOLÓGICO DE ATLETAS COM BASE NO ALGORITMO DE REDE NEURAL BACKPROPAGATION

INVESTIGACIÓN SOBRE LA CAPACIDAD DE AJUSTE PSICOLÓGICO DE LOS ATLETAS BASADA EN EL ALGORITMO DE RED NEURONAL BP

ABSTRACT

Athletes’ psychological control ability directly affects competitions. Therefore, it is necessary to supervise the athletes’ game psychology. Athletes’ game state supervision model is constructed through the facial information extraction algorithm. The homography matrix and the calculation method are introduced. Then, two methods are introduced to solve the rotation matrix from the homography matrix. After the rotation matrix is solved, the method of obtaining the facial rotation angle from the rotation matrix is introduced. The two methods are compared in the simulation data, and the advantages and disadvantages of each algorithm are analyzed to determine the method used in this paper. The experimental results show that the model prediction accuracy reaches 70%, which can effectively supervise the psychological state of athletes. This research study is of great significance to improve the performance of athletes in competitions and improve the application of back propagation (BP) neural network algorithm.

Neural Networks, Computer; Athletes; Handling, Psychological