MODELLING OF THE TECHNICAL ACTIONS OF TRACK AND FIELD ATHLETES SPECIALIZING IN RACE WALKING IN THE SYSTEM OF LONG-TERM PREPARATION
DOI:
https://doi.org/10.32782/spectrum/2024-1-2Keywords:
biomechanical characteristics, technical training, race walking, long-term improvement system, neural networks, modelingAbstract
One of the priority directions for optimizing the process of technical preparation of track and field athletes who specialize in race walking in the system of long-term improvement is the creation of well-defined criteria for improving the technical actions of athletes using modern modeling technologies. Today, neural networks are among the most advanced modeling technologies used in sports and athletics in particular. Objective. Improving the technical training of track and field athletes who specialize in race walking based on computer modelling of the technical actions of athletes in the long-term training system using artificial neural networks. Methods. Analysis of scientific and methodological literature, video recording with biomechanical computer analysis of athletes’ motor actions, modelling, and methods of mathematical statistics. The results. Informative anthropometric and biomechanical characteristics of the technique of track and field athletes specializing in race walking at the first and second stages of long-term training were analyzed. The biomechanical analysis of technical actions was carried out based on video footage of the 2014–2021 race walking championships of Ukraine in different age groups at the first and second stages of long-term training for men at distances of 3, 10 and 20 km and for women at distances of 2, 10 and 20 km. 181athletes were involved in the study: men – 98, of which 31 are at the distance of 3 km, 36 – 10 km, and 31 – 20 km; 83 women, 20 of them at the distance of 2 km, 32 – 10 km, and 31 – 20 km. As a result, a technology for modelling the technical actions of track and field athletes specializing in race walking in a system of long-term training via artificial neural networks was developed. The simulation algorithm, which allows modelling and forecasting the level of sports results at all levels (generalized, group, and individual) depending on gender at various stages of long-term improvement was presented. Multifunctional biomechanical models of the technique of track and field athletes specializing in race walking in the system of long-term training were elaborated.
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