Research on the Application of Improved Genetic Algorithm in the Design of Physical Education Teaching Systems

In colleges and universities in China, physical education is a crucial public fundamental subject. Traditional instruction often takes place during the designated class period in the training program. The instructor imparts to the pupils the principles of physical education so that they may become proficient in sports and ultimately raise their physical and athletic abilities. To lessen the issue of the basic genetic algorithm for intelligent grouping systems' delayed convergence and partial convergence, an enhanced genetic algorithm is suggested. By consistently rejecting comparable candidates, the algorithm may quickly expand the search field and guarantee the stability and diversity of the group. As a result, this work suggests a novel approach to intelligent grouping that is based on an enhanced genetic algorithm. Compared to the conventional algorithm, the novel approach is more effective and straightforward in resolving the issue of the algorithm's early convergence. Numerous tests have demonstrated how effectively the suggested algorithm satisfies every need for physical education. Test papers with a moderate level of difficulty and a sensible structure can be automatically generated by the genetic algorithm.