An algorithmic study of periodization strategy optimization in combined anaerobic and anaerobic fitness training for improving athletes’ endurance qualities

Abstract

The principle of flexibility and change should be adopted in the process of physical training, and the optimization of periodization training strategy can only be reasonably carried out according to the specific training response of athletes in order to improve the overall athletic ability of athletes. This paper utilizes the sports training pyramid as a guide, scrutinizes the endurance qualities athletes should possess, and suggests an optimization process for the periodization training strategy, which integrates multiple elements of periodization training. Based on the physiological characteristic indexes of athletes’ cardiorespiratory endurance, a model of cardiorespiratory endurance with different periodization training and different frequencies was established, and the results of the model were inputted into a BP network model optimized by the artificial fish swarm algorithm, thus realizing the prediction of the athletes’ cardiorespiratory endurance. The maximum value of the athletes’ endurance predicted by the ASFA-BP model was 81.09N, which differed from the actual value of the athletes’ endurance only by 1.58%, and the difference in the average lung capacity index (ALCI) was only 1.58%. The difference in mean spirometry index fluctuated between [0.16 mL/kg and 0.29 mL/kg]. The optimal duration of the periodization training strategy based on the acquired endurance data was between 10 and 18 days, and the exercise training load should be reduced by approximately 46% to 65%. The effective prediction of athletes’ endurance quality can help optimize the periodization training strategy and improve athletes’ competitive level faster.