<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In the context of artificial intelligence technology, the declining physical fitness of Chinese college students is still a serious social problem, and it is urgent to improve the physical health of college students. In this paper, the K-menns algorithm and decision tree CART algorithm are selected to be applied to the analysis and evaluation of college students’ physical health data based on the actual range of attributes of college students’ physical health data, the specific ideas of big data mining algorithm, and the characteristics and application fields of the algorithm are fully considered. Then, in the analysis of the physical health test data of class students, the percentage of the specific index amount to the total index amount is calculated, and the superior and inferior indexes are derived so as to realize the diagnosis of physical health posture. In order to investigate the correlation between physical exercise behavior and the health level of college teachers, a correlation analysis was conducted between the scores of 5 dimensions of physical exercise quality of college teachers and the scores of 8 dimensions of health level. The results showed that among the 5 dimensions, except for the behavioral intention and behavioral control dimensions, which did not have a statistically significant correlation with the physiological function dimension of health level, each of the remaining dimensions had a highly significant positive correlation with each dimension of health level P&lt;0.01. This study promotes the modernization of physical fitness assessment of college students, which is important for maintaining health.</p>
</abstract>

In the context of artificial intelligence technology, the declining physical fitness of Chinese college students is still a serious social problem, and it is urgent to improve the physical health of college students. In this paper, the K-menns algorithm and decision tree CART algorithm are selected to be applied to the analysis and evaluation of college students’ physical health data based on the actual range of attributes of college students’ physical health data, the specific ideas of big data mining algorithm, and the characteristics and application fields of the algorithm are fully considered. Then, in the analysis of the physical health test data of class students, the percentage of the specific index amount to the total index amount is calculated, and the superior and inferior indexes are derived so as to realize the diagnosis of physical health posture. In order to investigate the correlation between physical exercise behavior and the health level of college teachers, a correlation analysis was conducted between the scores of 5 dimensions of physical exercise quality of college teachers and the scores of 8 dimensions of health level. The results showed that among the 5 dimensions, except for the behavioral intention and behavioral control dimensions, which did not have a statistically significant correlation with the physiological function dimension of health level, each of the remaining dimensions had a highly significant positive correlation with each dimension of health level P<0.01. This study promotes the modernization of physical fitness assessment of college students, which is important for maintaining health.

Correlation analysis between the quality of physical activity and public health based on artificial intelligence technology

Applied Mathematics and Nonlinear Sciences

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

In the context of artificial intelligence technology, the declining physical fitness of Chinese college students is still a serious social problem, and it is...

Correlation analysis between the quality of physical activity and public health based on artificial intelligence technology

Data publikacji: 04 paź 2023

Zakres stron: -

Otrzymano: 02 gru 2022

Przyjęty: 14 kwi 2023

DOI: https://doi.org/10.2478/amns.2023.2.00486

Słowa kluczowe
K-menns, Decision tree CART, Physical activity quality, Evaluation index system, Correlation

© 2023 Yong Wang, published by Sciendo

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

Correlation analysis between the quality of physical activity and public health based on artificial intelligence technology

Data publikacji: 04 paź 2023

Zakres stron: -

Otrzymano: 02 gru 2022

Przyjęty: 14 kwi 2023

DOI: https://doi.org/10.2478/amns.2023.2.00486

Słowa kluczoweK-menns, Decision tree CART, Physical activity quality, Evaluation index system, Correlation

© 2023 Yong Wang, published by Sciendo

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

Słowa kluczowe
K-menns, Decision tree CART, Physical activity quality, Evaluation index system, Correlation