Frontiers in Sport Research, 2023, 5(3); doi: 10.25236/FSR.2023.050305.
Li Yiding
University of Commerce Boustead College, Xiqing, Tianjin, 300384, China
With the in-depth study of physical training, people analyze it from all aspects and draw some rules. At the same time, there are many problems to be solved urgently. People began to explore the role of modern new technologies and new means in physical training, such as using big data technology, but they did not solve all the problems in physical training, but they can be sure that the future physical training will be efficient and scientific. Physical training is one of the important contents of the curriculum for students majoring in physical education in colleges and universities, and it is also the core issue of training theory and the key to improve sports performance. Through long-term training practice, it has been found that the improvement of physical fitness plays a very important role in improving the comprehensive ability of athletes. In the future, most students majoring in physical education will engage in front-line teaching or sports training. Therefore, the knowledge and skills reserve of physical fitness training for students majoring in physical education is particularly important. In response to this, the paper proposes a quantitative and personalized physical training organization and management method based on management information systems, designs a physical training management information system based on the actual situation of military academy joint training students, and proposes corresponding physical training management measures. Experimental results show that the data mining algorithm designed in this paper can more efficiently and reasonably formulate athletes' training plans.
Big data analysis; College student; Physical fitness training; Scheme decision
Li Yiding. Research on College Students' Physical Training Scheme Decision Based on Big Data Analysis. Frontiers in Sport Research (2023) Vol. 5, Issue 3: 29-33. https://doi.org/10.25236/FSR.2023.050305.
[1] Wang F. Research on physical fitness of college students based on big data and intelligent campus [J]. Basic & clinical pharmacology & toxicology. 2019, 10(1):12-14.
[2] Chu T. Research on College Students' Physique Testing Platform Based on Big Data Analysis [J]. Mathematical Problems in Engineering, 2022, 3(3):16-18.
[3] Monroig A C, Chen H C, Carraccio C, et al. Medical Students' Perspectives on Entrustment Decision-Making in an EPA Assessment Framework: A Secondary Data Analysis[J]. Academic Medicine, 2020, 33(8):42-48.
[4] Che Y, Che K, Li Q. Application of Decision Tree in PE Teaching Analysis and Management under the Background of Big Data [J]. Computational intelligence and neuroscience, 2022, 8(3):38-40.
[5] Jin Yin, Xiaoqiu, et al. Study on safety mode of dragon boat sports physical fitness training based on machine learning – Science Direct [J]. Safety Science, 2019, 120(3):1-5.
[6] Luo L, Guo M, Huang J, et al. Research on the Effect of an Entrepreneurial Environment on College Students' Entrepreneurial Self-Efficacy: The Mediating Effect of Entrepreneurial Competence and Moderating Effect of Entrepreneurial Education [J]. Sustainability, 2022,22(5):41-45.
[7] Chelsea S, Kenji D, Brian H, et al. Effect of Exercise Training Programs on Physical Fitness Domains in Military Personnel: A Systematic Review and Meta-Analysis[J]. Military Medicine. 2022, 30(4): 9-10.
[8] Wang H, Wang N, Li M J, et al. Student Physical Health Information Management Model under Big Data Environment[J]. Scientific Programming, 2021, 5(1):1-10.
[9] Li X, Song C, Rochester C A, et al. Construction of a Complex System Based on Big Data for the Intelligent Service System of Youth Physical Health [J]. Complexity, 2021, 2(4):11-18.
[10] Guo C, Suo J, Xu C, et al. Data Analysis of Physical Fitness Monitoring Based on Mathematical Models[J]. Mathematical Problems in Engineering, 2021, 62(3):17-30.