Algorithm Study on Physical Adaptive Regulation Based on BP Neural Network

As a kind of empirical model, artificial neural network is playing an increasingly important role in the actual theoretical research and practical development. On the basis of principles, this paper has analyzed the model structure of artificial neural network and its related properties, and has made further analysis of the network structure of BP algorithm and its detailed derivation process. Based on this, the paper has made a comparative analysis on the improvement of the three algorithms, and has applied the method for self-regulation learning rate into the empirical analysis of the effectiveness of athletes physical strength by combining with the realities. Finally, the results show that the method has got the obvious effect, and can provide theoretical and technical support, to a certain extent, for the research of the related fields.