In order to solve the relationship between youth aerobic exercise and obesity reduction, an improved ant colony algorithm-oriented aerobic exercise method was proposed. Firstly, the changes in body shape, weight, BMI, body fat, body circumference, and other indicators of obese adolescents before and after aerobic exercise were used as the initial pheromone distribution matrix, and the random evolution factor and evolutionary drift threshold were introduced to establish the target function of reducing obesity caused by aerobic exercise in adolescents. The constraint conditions of the relationship between aerobic exercise and adolescent obesity reduction were explained, and the particle algorithm was introduced to establish the optimal model of aerobic exercise for adolescent obesity reduction. The experimental results show that with the increasing number of experiments, the advantages of this method are more obvious. From the overall level, the average modeling error of this method is about 0.053%, while the average error of the traditional method is about 0.186%, which shows that this method can control the error within a reasonable range, and it is proved that the improved ant colony algorithm can have a good correlation with the method of aerobic exercise.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8959987PMC
http://dx.doi.org/10.1155/2022/9957916DOI Listing

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