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

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.

Automated summary

This article explores sports training adaptation theory based on self-organization theory and neural network models, utilizing modern technological advancements and scientific training methods to establish an evaluation model for athletes' training adaptation status. The successful application of self-organization theory in sports training is demonstrated through the designed self-organizing competitive neural network.