• DocumentCode
    1618368
  • Title

    Artificial Neural Networks As a Tool of Modeling of Training Loads

  • Author

    Rygula, Igor

  • Author_Institution
    Univ. Sch. of Phys. Educ., Katowice
  • fYear
    2006
  • Firstpage
    2985
  • Lastpage
    2988
  • Abstract
    This paper shows that extremely important element of forming speed capabilities is proper (quantitative) structure of exercise loads. This means that training means should be chosen from point of view of energy production in metabolic processes, which depends on the structure of training means from the information area and energy area, therefore on the character of work made, its intensity, duration of exercise, number of repetitions and duration of rest periods. From the training process effectiveness point of view, it is extremely important to find the correct tool for choosing means in given training cycle. The investigation results confirm the experiences of coaches and theorists of sport, that the structure of volume and intensity of exercise loads should be individually chosen with consideration of predispositions of separate athletes. Individualization of training is condition for its optimization
  • Keywords
    biology computing; biomechanics; neural nets; sport; artificial neural networks; athletes; energy production; exercise duration; exercise intensity; exercise loads; metabolic processes; speed capabilities; training loads; Artificial neural networks; Explosives; Load modeling; Mathematical model; Muscles; Nervous system; Optimal control; Production; Shape measurement; Standards development; artificial neural networks; modeling; optimal control; speed capabilities; sport training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
  • Conference_Location
    Shanghai
  • Print_ISBN
    0-7803-8741-4
  • Type

    conf

  • DOI
    10.1109/IEMBS.2005.1617101
  • Filename
    1617101