THE USE OF ARTIFICIAL NEURAL NETWORKS IN SUPPORTING THE ANNUAL TRAINING IN 400 METER HURDLES

• Authors: Janusz Iskra , Krzysztof Przednowek , Krzysztof Wiktorowicz , Tomasz Krzeszowski
• Languages of publication: EN

Abstracts

EN

This paper presents an evaluation of the annual cycle for 400 m hurdles using artificial neural networks. The analysis included 21 Polish national team hurdlers. In planning the annual cycle, 27 variables were used, where 5 variables describe the competitor and 22 variables represent the training loads. In the presented solution, the task of generating training loads for the assumed result were considered. The neural models were evaluated by cross-validation method. The smallest error was obtained for the radial basis function network with nine neurons in the hidden layer. The performed analysis shows that at each phase of training the structure of training loads is different.

Keywords

EN

400 meter hurdles; artificial neural networks; planning training loads

Discipline

• MEDICINE: MEDICINE

• Publisher: Uniwersytet Szczeciński. Wydawnictwo Naukowe Uniwersytetu Szczecińskiego
• Journal: Central European Journal of Sport Sciences and Medicine
• Year: 2017
• Volume: 17
• Issue: 1
• Pages: 15-24

Contributors

author

Janusz Iskra

• Faculty of Physical Education and Physiotherapy, Opole University of Technology

author

Krzysztof Przednowek

• Faculty of Physical Education, University of Rzeszow

author

Krzysztof Wiktorowicz

• Faculty of Electrical and Computer Engineering, Rzeszow University of Technology

author

Tomasz Krzeszowski

• Faculty of Electrical and Computer Engineering, Rzeszow University of Technology

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• Document Type: article