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<p>In recent years, the physical fitness of college students has been declining year by year, which has become the focus of national concern. In this paper, firstly, the human body motion tracking based on a multi-objective optimization algorithm is applied in the auxiliary training of college students’ sports to provide data support for the formulation of sports plans, and the Chebyshev function evolution calculation is used to obtain the Pareto optimal solution for sports training. Secondly, the similarity function between the two-dimensional projection of the skeleton and the silhouette of the image is established in the constructed human body model so as to calculate the multi-objective optimization function. The optimized training plan was specifically analyzed after analyzing the sports assessment of college students in X school. The results show that compared with the conventional training plan, the optimized training plan has more sports load intensity indexes distributed between 1.5 and 2.0, indicating that the plan is more scientific and effective. The research presented in this paper can be a valuable resource for the creation of sports programs for college students.</p>
</abstract>

In recent years, the physical fitness of college students has been declining year by year, which has become the focus of national concern. In this paper, firstly, the human body motion tracking based on a multi-objective optimization algorithm is applied in the auxiliary training of college students’ sports to provide data support for the formulation of sports plans, and the Chebyshev function evolution calculation is used to obtain the Pareto optimal solution for sports training. Secondly, the similarity function between the two-dimensional projection of the skeleton and the silhouette of the image is established in the constructed human body model so as to calculate the multi-objective optimization function. The optimized training plan was specifically analyzed after analyzing the sports assessment of college students in X school. The results show that compared with the conventional training plan, the optimized training plan has more sports load intensity indexes distributed between 1.5 and 2.0, indicating that the plan is more scientific and effective. The research presented in this paper can be a valuable resource for the creation of sports programs for college students.

Research on the development of college students’ sports program based on multi-objective optimization algorithm

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

In recent years, the physical fitness of college students has been declining year by year, which has become the focus of national concern. In this paper,...

Research on the development of college students’ sports program based on multi-objective optimization algorithm

Publié en ligne: 31 janv. 2024

Pages: -

Reçu: 11 déc. 2023

Accepté: 20 déc. 2023

DOI: https://doi.org/10.2478/amns-2024-0021

Mots clés
Multi-objective optimization, Human motion tracking, Pareto optimal solution, Chebyshev function, Exercise load

© 2024 Shuai Song, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on the development of college students’ sports program based on multi-objective optimization algorithm

Publié en ligne: 31 janv. 2024

Pages: -

Reçu: 11 déc. 2023

Accepté: 20 déc. 2023

DOI: https://doi.org/10.2478/amns-2024-0021

Mots clésMulti-objective optimization, Human motion tracking, Pareto optimal solution, Chebyshev function, Exercise load

© 2024 Shuai Song, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
Multi-objective optimization, Human motion tracking, Pareto optimal solution, Chebyshev function, Exercise load