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Evaluation of fitness state of sports training based on self-organizing neural network

  • S.I. : SPIoT 2020
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Abstract

Self-organization theory has become a hotspot in system engineering scientific theoretical research. However, there are few studies on autonomous adaptation to sports training from the perspective of self-organization theory, and the application of self-organizing neural network models in sports training is relatively rare. Guided by multidisciplinary knowledge and various scientific principles, this article uses modern scientific and technological achievements and adopts scientific training methods and means to implement optimal control over the entire process of sports training. Moreover, this article uses a self-organization theory that has the characteristics of new things and has been successfully used in other fields and neural network models to study sports training adaptation theory. The evaluation model of athletes' training adaptation status established by a self-organizing competitive neural network designed by self-organization principle also proves the feasibility of applying self-organization theory to sports training adaptation.

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Authors and Affiliations

  1. Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, 271016, Shandong, China

    Huai Liang

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  1. Huai Liang
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Correspondence to Huai Liang.

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Liang, H. Evaluation of fitness state of sports training based on self-organizing neural network. Neural Comput & Applic 33, 3953–3965 (2021). https://doi.org/10.1007/s00521-020-05551-w

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  • DOI: https://doi.org/10.1007/s00521-020-05551-w

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