Personalized Training Path Design for Civil Aviation Flight Cadet Physical Education Course Based on Genetic Algorithm

Abstract The design of sports courses for civil aviation flight cadets is affected by factors such as the class site, the number of students, and the personalized characteristics of the students. This paper proposes a sports course combination method based on chaotic real number genetic algorithm to realize the personalized training path recommendation of sports courses for civil aviation flight students. Firstly, we collect the information data of flight trainees, model the constraints such as exercise load, and determine the objective function. Then for the problem of premature reproduction of excellent individuals caused by the limitations of genetic algorithm due to population size and other limitations, combined with the randomness and traversal of chaotic system, the population diversity is improved, and the sports course combination algorithm based on chaotic genetic algorithm is constructed. The traditional GA takes 115.8 seconds when the number of occurrence of better solutions tends to be stable, while the algorithm in this paper takes only 28.6 seconds, and the number of better solutions is much higher than that of GA. Through experimental verification, the improved genetic algorithm realizes the personalization of the sports courses for civil aviation flight trainees and satisfies the constraints. This study has positive significance for improving the efficiency of civil aviation sports course scheduling and realizing personalized training for flight cadets.