Abstract
A training simulation system based on computer simulation AI intelligence technology is designed to improve football players’ training efficiency and performance. The system includes a perception interaction subsystem and a model calculation subsystem. The perception interaction subsystem builds a three-dimensional training scene through a virtual environment generator and then renders the scene in the model calculation subsystem’s view module. At the same time, the logic module calculates the decline in the athlete’s physical fitness. The calculation results are then passed back to the perception interaction subsystem’s effect generator to present the interactive effects of the athlete’s training. Tests show that the system can effectively perform athlete’s physical fitness decay calculations, has good load-bearing capacity, can enhance the physical training effect of football players and improve simulation efficiency. The application of this system can improve athletes’ competition performance.
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References
Zavalishina, S.Y., Makurina, O.N., Mal, G.S., et al.: Influence of systematic football training on adolescent functional characteristics. Biomed. Pharmacol. J. 14(2), 533–540 (2021)
Chomani, S.H., Joksimovi, M., Lili, A., et al.: Effect of aquatic plyometric training on motor ability in youth football players. Health Sport Rehabil. 7(1), 66–76 (2021)
Bi, Y., Ling, J.I.A., Wang, Q.: Formulation of scheme for sports training management based on system dynamics. In: 2016 4th International Conference on Machinery, Materials and Information Technology Applications, pp. 1193–1196. Atlantis Press (2017)
Cao, Y., Mao, H.: High-dimensional multi-objective optimization strategy based on directional search in decision space and sports training data simulation. Alex. Eng. J. 61(1), 159–173 (2022)
Fischerova, P., Nitychoruk, M., Smolka, W., et al.: The impact of strength training on the improvement of jum** ability and selected power parameters of the lower limbs in soccer players. Baltic J. Health Phys. Act. 13(1), 5–9 (2021)
Szymanek-Pilarczyk, M.: The effects of supplementary plyometric training on the development of selected motor skills of young football players from Akademia Raków Czstochowa football club. Sport i Turystyka Środkowoeuropejskie Czasopismo Naukowe 4(1), 129–138 (2021)
Özkamçi, H., Zileli, R., Diker, G., et al.: Investigation of some performance parameters of professional football players according to game regions. Pakistan J. Med. Health Sci. 15(5), 1699–1702 (2021)
Kayhan, R.F., Ikikci, A., Glez, O.: The effect of reactive strength index on some parameters of young elite football players. Int. J. Sport Exerc. Training Sci. (12), 88–91 (2021)
Atl, A.: Comparison of certain physical and performance parameters of young football players based on positions. J. Educ. Issues 7(1), 19–21 (2021)
Ovcharenko, S., Yakovenko, A., Sydorchuk, T., et al.: Criteria for assessing the level of physical fitness and physical state of football players with cerebral paralysis, taking into account their sports classes. Pedagogy Phys. Cult. Sports 25(2), 125–131 (2021)
Chu, W.C.C., Shih, C., Chou, W.Y., et al.: Artificial intelligence of things in sports science: weight training as an example. Computer 52(11), 52–61 (2019)
Zhao, Z., Liu, X., She, X.: Artificial intelligence based tracking model for functional sports training goals in competitive sports. J. Intell. Fuzzy Syst. 40(2), 3347–3359 (2021)
Hammes, F., Hagg, A., Asteroth, A., et al.: Artificial intelligence in elite sports—a narrative review of success stories and challenges. Front. Sports Active Living 4, 861466 (2022)
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Zhang, Q., Yu, L. (2024). Football Players’ Physical Parameter Simulation Training Based on AI Intelligent Simulation. In: Pichappan, P., Rodriguez Jorge, R., Chung, YL. (eds) Advances in Real-Time Intelligent Systems. RTIS 2023. Lecture Notes in Networks and Systems, vol 950. Springer, Cham. https://doi.org/10.1007/978-3-031-55848-1_18
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DOI: https://doi.org/10.1007/978-3-031-55848-1_18
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