Characteristic Analysis of Cheerleading Self-selected Action Arrangement Elements Based on BP Neural Network

Abstract

Abstract BP neural network is a typical algorithm in artificial intelligence networks, and it has strong nonlinear mapping ability, solving some nonlinear problems and pattern recognition is its most prominent part. The network topology of the BP neural network is simple, it has high error precision, it is easy to program, and also has strong operability, it is one of the most important algorithms in the field of data mining. Cheerleading is one of the dance cheerleading events, because of its sunshine, fashion and vitality, it has become a new sports event on campus, although cheerleading has developed rapidly in China, its promotion on campus is still at the initial stage, with the increasing number of public contestants, the competition among the participating teams has become increasingly fierce, excellent choreography is the key to victory, by using the methods of literature, video analysis and mathematical statistics, the author made an in-depth analysis of the top eight teams, including 24 teams, who achieved the best in the collective flower ball optional complete set of actions in the three open national cheerleading championships from 2019 to 2021, grasp the current situation and trend of the arrangement of free flower ball movements in the open children’s group, and summarize its rules, it provides a theoretical basis for the arrangement of the set of collective flower ball optional movements of the open university group, improve the overall level of the flower ball cheerleading program of the open university group, and play a role in consolidating the basic learning of flower ball cheerleading.