Soccer Curveball Trajectory Optimized by Adaptive Fuzzy Algorithm

Football, as the world’s largest sport, plays an important role in the improvement of modern society. Fuzzy algorithms simulate human thinking, avoid the difficulty of creating mathematical models, and can use simplified designs to complete more complex tasks. This paper studies a multi-modal and motion modeling-based model and an overall algorithm for soccer trajectory prediction based on adaptive online adjustment of parameters to achieve The automatic optimization of the motion trajectory model is realized, the generation of the model parameter library and the training of the model parameters are realized. The purpose is to predict the trajectory of the football arc based on the adaptive fuzzy algorithm, through a large amount of experimental data and the decision tree algorithm in the machine learning algorithm, and at the same time use the target space positioning, starting from the actual needs of the football positioning vision system, to achieve The fast and accurate football identification and positioning has laid a good foundation for the subsequent motion trajectory analysis.