Abstract
In order to study the effect of aerobic training exercise on cardiopulmonary function of the human body, in this study, multiple linear regression based on the particle swarm optimization cardiopulmonary function test method of constructing the sports cardiopulmonary function test model is used. The traditional multiple linear regression after 41 iteration achieves convergence, and after the particle swarm optimization, about 25 times, convergence is achieved. Moreover, the convergence error of pSO is less than that of traditional multiple linear regression algorithm, which verifies the effectiveness of PSO. This method can effectively detect cardiopulmonary function of athletes before and after aerobic training, and the modeling accuracy is high, and the detection performance of cardiopulmonary function of aerobic training is better than the traditional relational model algorithm, which provides a new way for cardiopulmonary model detection of the human body.