Research on Scientific Training Model of Basketball Tactics Based on Swarm Intelligence Algorithm

Starting from the practical aspect of basketball, this article constructs the content and classification model of the basketball tactical system, deepens the understanding and grasp of the competitive rules of basketball, and provides scientific guidance for the construction of basketball scientific training theory and basketball training practice. Method: This research is based on computer swarm intelligence algorithms, and conducts systematic research on the basketball tactical system. Results: The basketball tactical system model and its characteristics under the field of vision of computer swarm intelligence algorithms are achieved. The optimization of neural networks through intelligent algorithms establishes a neural network prediction model based on swarm intelligence algorithms to make offline predictions for biochemical variables that are difficult to measure online. Simulation results prove that the convergence speed is significantly higher, the robustness is good, and the characteristics of the model are the continuity, mutual dominance and asymmetry of offensive and defensive transitions, and the variability and degree of risk difference in offensive and defensive transitions.