Test System for Computer Intelligent Simulation of Athlete’s Physical Adaptation Ability to the Environment

The ability of the body to adapt to the environment can help athletes better adapt to different climates and altitudes, resulting in more stable and outstanding performance in competitions. Moreover, the ability of the body to adapt to the environment can improve the endurance and stress resistance of athletes, enabling them to maintain a high-level competitive state in various environments. This article measured the physical adaptability of athletes to the environment and understood the basic characteristics that affect their athletic performance in different environments. Artificial neural network technology was applied to construct a prediction model for the body’s ability to adapt to the environment, improve the accuracy of measuring the body’s ability to adapt to the environment, and better guide athletes in physical and tactical training, enriching the field of sports training and making it better serve sports practice. The experimental results showed that the accuracy of the ANN (artificial neural network) algorithm based athlete’s body adaptation ability to the environment in the test set was 90.12%, which was higher than PSO (Particle Swarm Optimization) algorithm and ACO (Ant Colony Optimization) algorithm.