Received 02.12.2021, Revised 24.02.2022, Accepted 24.03.2022

Study of methods for calculating the performance of a shot putter athlete

Oleksandr Melnykov, Mykyta Kadatskyi

The concept of shot put, the structure of the shot put sector, the study of the results of the shot putters of Ukraine and the world arena, the description of the shooting technique "from the jump", the use of the concept of computer vision in sports are considered. The models and methods for calculating the performance of a shot putter athlete, models for calculating the shot put "from the spot" and "from the jump", the main tasks for the apparatus of neural networks and the use of the concept of computer vision to create a video analysis system are analyzed. The main task and purpose of the work is set. The formalization and algorithm of the neural network model for evaluating the pushing phases is presented. The created information model of the designed system is described in the language of visual modeling UML - diagrams of use cases, classes, cooperation, sequence, states and components are given. The possibilities of the system for studying the main indicators of a shot putter athlete, the possibility of using a video system to improve the technique of pushing are described. An example of the operation of this system is given and an analysis of the calculation results is carried out

shot put, the most effective shot put technique, physic-mathematical model of shot put, direct neural networks, python, Lazarus, mediapipy, neurolab
101-110
Melnykov, O., & Kadatskyi, M. (2022). Study of methods for calculating the performance of a shot putter athlete. Information Technologies and Computer Engineering, 19(2), 101-110. https://doi.org/10.31649/1999-9941-2022-53-1-101-110

References

[1] Tutevich, V.N. (1956). Theory of sports throwing. Moscow: FiS.

[2] Tutevich, V.N. (1955). Shot Put. Moscow: FiS.

[3] Kasyuk, S.T., & Vakhtomova, E.M. (2013). Using neural networks for data analysis and forecasting in physical culture and sports. Scientific and Theoretical Journal “Scientific Notes”, 12(106), 72-77.

[4] Schaa, W. (2010). Biomechanical analysis of the shot put at the 2009 IAAF World Championships in Athletics. New Studies in Athletics, 3-4, 9-21.

[5] Melnikov, A.Yu., & Kadatsky, N.A. (2019). Using neural network technologies for approximate determination of the indicators of a shot thrower. In Automation and computer-integrated technologies in production and education: Status, achievements, development prospects: Materials of the All-Ukrainian scientific and practical Internet conference (pp. 87-89). Cherkasy: Cherkasy National University named after Bohdan Khmelnytsky.

[6] Kadatsky, M.A., & Melnikov, O.Yu. (2020). Development of performance indicators of a shot thrower using a custom neural network with 14 input factors. In G.O. Raiko (Eds.), Use of information and communication technologies in the modern digital society: Materials of the international conference. scientific-practical conference (pp. 280-283). Kherson: Publishing house of FOP Vishemirsky V.S.

[7] What is computer vision? (2021). Retrieved from : https://www.ibm.com/topics/computer-vision.

[8] Kadatskyi, M.A., Melnikov, O.Yu. (2021). Setting the problem of determining the best throwing technique for a shot put athlete using the concept of computer vision. In G.O. Raiko (Eds.), Modern computer systems and networks in management: Materials of the IV all-ukrainian scientific and practical internet conference of students, graduate students and young of scientists (pp. 225-228). Kherson: Publishing house of FOP Vishemirsky V.S.

[9] Melnikov, A.Yu., & Kadatskyi, N.A. (2019). Development of an information system for the approximate determination of the indicators of an athlete-thrower with the help of mathematical modeling of core pushing and the application of neural network technologies. Bulletin of the Donbas State Machine-Building Academy: Collection of Scientific Works, 2(46), 145-149.

[10] Melnikov, A.Yu., & Kadatskyi, N.A. (2021). Creation of a neural network modeling module in a decision support system for calculating the performance of a shot put athlete. In Information technologies in culture, art, education, science, economy and business: Materials VI International scientific and practical conference (pp. 183-186). Kyiv: KNUKiM Publishing Center.