Research on Intelligent Algorithm System of Motion Formation Path Under Computer Simulation

At present, Chinese academic circles pay more and more attention to computer simulation technology. Computer simulations can lead to new and efficient training methods for athletes and coaches. Due to the problems of high cost and low controllability in group training with rehearsal mode, this project intends to use cellular automata to study the multi-objective particle swarm optimization method and apply it to team training. Two evaluation indexes of cellular automata model and moving path “good” and “bad” are introduced. The dynamic adjustment of moving path is realized by using the shortest path length and the best path as the optimization criteria. The MOPSO-CA algorithm is applied to the formation arrangement and transformation of the team gymnastics, and the self-organization and coordination characteristics of the intelligent group are fully utilized, and the optimal formation transformation path is independently explored. This paper expounds the process, basic idea and algorithm flow of environment modeling of group gymnastics formation transformation based on MOPSO-CA algorithm. The performance comparison test and 3D simulation experiment are carried out. Simulation experiments show that the improved optimization method can effectively improve the optimization, convergence and interaction with the outside world or other people.