Application of Big Data Analysis in Model Construction to Prevent Athlete Injury in Training

[1] Liu, K., Li, X., & Rochester, C. A. (2022). Relationship between physical training and tactical training in sports training relying on boosting and bagging algorithms. Scientific programming(Pt.10), 2022. Search in Google Scholar

[2] Zhang, L., Xie, J., Antonidoss, A., & Anbarasan, M. (2021). Activity classification and analysis during sports training session using fuzzy model. Journal of Intelligent and Fuzzy Systems(5), 1-15. Search in Google Scholar

[3] Bai, Y., & Chen, Y. (2021). Human motion analysis and action scoring technology for sports training based on computer vision features. Journal of Intelligent and Fuzzy Systems(34), 1-9. Search in Google Scholar

[4] Huang, X., Sheng, K., & Hu, Y. (2019). Key factors influencing ecological operation risk of football sports. Ekoloji, 28(107), 3715-3720. Search in Google Scholar

[5] Martí Casals, & Finch, C. F. (2017). Sports biostatistician: a critical member of all sports science and medicine teams for injury prevention. Injury Prevention. Search in Google Scholar

[6] Zaremski, J. L., Pazik, M., Dean, C. W., Vijayaraghavan, N., & Horodyski, M. B. (2021). Forearm flexor injury is associated with medial ucl injury in throwing athletes. PM&R. Search in Google Scholar

[7] Tak, Igor, J., & R. (2018). Hip and groin pain in athletes: morphology, function and injury from a clinical perspective. British Journal of Sports Medicine. Search in Google Scholar

[8] Eckard, T. G., Padua, D. A., Hearn, D. W., Pexa, B. S., & Frank, B. S. (2018). The relationship between training load and injury in athletes: a systematic review. Sports Medicine, 48, 1-33. Search in Google Scholar

[9] Jungmalm, J., Bertelsen, M. L., & Nielsen, R. O. (2019). What proportion of athletes sustained an injury during a prospective study? censored observations matter. British Journal of Sports Medicine, 54(2), bjsports-2018-100440. Search in Google Scholar

[10] Wang, P. (2021). Research on sports training action recognition based on deep learning. Scientific Programming. Search in Google Scholar

[11] Xu, Y. (2021). A sports training video classification model based on deep learning. Scientific Programming, 2021(5), 1-11. Search in Google Scholar

[12] Teer, B. (2020). Performance analysis of sports training based on random forest algorithm and infrared motion capture. Journal of Intelligent and Fuzzy Systems, 40(12), 1-11. Search in Google Scholar

[13] Guo, Q., & Li, B. (2020). Role of ai physical education based on application of functional sports training. Journal of Intelligent and Fuzzy Systems(2), 1-9. Search in Google Scholar

[14] Jiang, H., & Tsai, S. B. (2021). An empirical study on sports combination training action recognition based on smo algorithm optimization model and artificial intelligence. Mathematical Problems in Engineering, 2021, 1-11. Search in Google Scholar

[15] He, F. (2021). Early warning model of sports injury based on rbf neural network algorithm. Complexity, 2021. Search in Google Scholar

[16] Tan, L., & Ran, N. (2023). Applying artificial intelligence technology to analyze the athletes’ training under sports training monitoring system. International Journal of Humanoid Robotics, 20(06). Search in Google Scholar

[17] Zhao, Z., Liu, X., & She, X. (2020). Artificial intelligence based tracking model for functional sports training goals in competitive sports. Journal of Intelligent and Fuzzy Systems, 40(1), 1-13. Search in Google Scholar

[18] Li, S., Liu, C., & Yuan, G. (2021). Martial arts training prediction model based on big data and mems sensors. Scientific Programming. Search in Google Scholar

[19] Wang, Z., Zheng, X., & Yang, Z. (2021). Data collection of safety accidents in sports training of athletes with internet of things technology. Journal of Intelligent and Fuzzy Systems, 1-7. Search in Google Scholar

[20] Huang, X., Li, H., Zhou, H., Krishnamoorthy, S., & Kadry, S. N. (2022). Activity classification and analysis during a sports training session using a fuzzy model. International Journal on Artificial Intelligence Tools. Search in Google Scholar

[21] Zhu, D., Zhang, H., Sun, Y., & Qi, H. (2021). Injury risk prediction of aerobics athletes based on big data and computer vision. Scientific Programming. Search in Google Scholar

[22] Wenying Zhou, Xue Han, Yanjun Wu, Guochao Shi, Shiqi Xu, Mingli Wang.. & Zelong Li. (2024). High-performance grating-like SERS substrate based on machine learning for ultrasensitive detection of Zexie-Baizhu decoction. Heliyon (9), e30499-e30499. Search in Google Scholar

[23] Shuangyi Wu & Sheng Meng. (2024). A Modern Communication Path for Traditional Chinese Cultural Design Concepts Based on AdaBoost Model. Applied Mathematics and Nonlinear Sciences(1). Search in Google Scholar

[24] Yi Xiao, Mengjie Jin, Guanqiu Qi, Wenming Shi, Kevin X. Li & Xianping Du. (2024). Interpreting the influential factors in ship detention using a novel random forest algorithm considering dataset imbalance and uncertainty. Engineering Applications of Artificial Intelligence(PE),108369-. Search in Google Scholar

[25] Sherril Sophie Maria Vincent & N. Duraipandian. (2024). Detection and prevention of sinkhole attacks in MANETS based routing protocol using hybrid AdaBoost-Random forest algorithm. Expert Systems With Applications(PC),123765-. Search in Google Scholar