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

IF 3.1 Q1 Mathematics Applied Mathematics and Nonlinear Sciences Pub Date : 2024-01-01 DOI:10.2478/amns-2024-0021
Shuai Song
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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.
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基于多目标优化算法的大学生体育项目开发研究
近年来,大学生体质逐年下降,已成为国家关注的焦点。本文首先将基于多目标优化算法的人体运动跟踪应用于大学生体育辅助训练中,为体育计划的制定提供数据支持,并利用切比雪夫函数演化计算得到体育训练的帕累托最优解。其次,在构建的人体模型中建立骨架二维投影与图像轮廓的相似函数,从而计算多目标优化函数。在分析了 X 学校大学生的体育考核情况后,对优化后的训练计划进行了具体分析。结果表明,与传统训练计划相比,优化后的训练计划的运动负荷强度指标更多分布在 1.5 至 2.0 之间,说明该计划更加科学有效。本文的研究成果对大学生体育项目的制定具有重要的参考价值。
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来源期刊
Applied Mathematics and Nonlinear Sciences
Applied Mathematics and Nonlinear Sciences Engineering-Engineering (miscellaneous)
CiteScore
2.90
自引率
25.80%
发文量
203
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