School of Culture and Media, Xinhua University, Hefei 230088, China.
J Environ Public Health. 2022 Sep 15;2022:4043876. doi: 10.1155/2022/4043876. eCollection 2022.
In the quality evaluation of public sports training, the selected indicators are not comprehensive, resulting in some errors in the results of quality evaluation. Therefore, this paper designs a public sports training quality evaluation method based on the deep learning model of global topology optimization. Determine the basic principles of public sports training quality evaluation, determine the human coordinate points of public sports training by determining the basic section and basic axis of human training, and extract the data of public sports training quality evaluation. On this basis, quantify the public sports training quality evaluation index, construct the evaluation matrix, calculate the weight of the evaluation index, and determine the importance of the public sports training quality evaluation index. Preprocess the public sports training quality evaluation index set, search the optimal fitness value in the global topology optimization depth learning model, introduce the global topology optimization depth learning model, input the evaluation index and output the evaluation quality results, and realize the quality evaluation of public sports training. The experimental results show that the evaluation method in this paper can improve the accuracy of the evaluation results and is feasible.
在公共体育培训质量评价中，由于选择的指标不全面，导致质量评价结果存在一些误差。为此，本文设计了一种基于全局拓扑优化深度学习模型的公共体育培训质量评价方法。确定公共体育培训质量评价的基本原则，通过确定人体训练的基本截面和基本轴，确定公共体育培训的人体坐标点，并提取公共体育培训质量评价数据。在此基础上，量化公共体育培训质量评价指标，构建评价矩阵，计算评价指标权重，确定公共体育培训质量评价指标的重要性。对公共体育培训质量评价指标集进行预处理，在全局拓扑优化深度学习模型中搜索最优适应值，引入全局拓扑优化深度学习模型，输入评价指标并输出评价质量结果，实现公共体育培训的质量评价。实验结果表明，本文提出的评价方法可以提高评价结果的准确性，具有可行性。
