Weight Control of Sports Training Chaos Predicting Model

As the sports training predicting model based on chaos local predicting method still has the low predicting accuracy and the slow function speed problems, this paper proposes a sports training chaos predicting model based on weight control ant colony algorithm. It firstly uses the comprehensive weight factor to perform the weight control to the initial information of the new join node in the ant colony algorithm, and then performs the optimizing iteration to the pheromone of weight control optimization, and updates the pheromone of ant node according to its contribution. Then the paper performs the optimization selection to the pheromone persistence parameters, the normalized factors and the relative importance factors to reduce the computing time and optimal error rate of the ant colony algorithm. Finally, adopt the improved ant colony algorithm to optimize the sports training chaos predicting model. The experiments show that the proposed sports training chaos predicting model based on weight control ant colony algorithm has a higher accuracy than the standard ant colony algorithm and the sports training chaos local predicting model.