Abstract
In order to improve the evaluation effect of sports training methods, this paper improves the traditional CSO algorithm to construct a sports training method evaluation model based on the improved CSO algorithm. Moreover, this paper combines actual needs to propose an improved chicken flock algorithm based on reverse learning and inertial weight reduction strategy, and uses the local sensitivity analysis theory to calculate the sensitivity of the parameters to be identified. Simultaneously, this paper divides the identification parameters into important identification parameters and secondary identification parameters, decouples the identification process, and identifies model parameters step by step to achieve the purpose of reducing the dimensions of the parameters to be identified and improving the accuracy of identification. In addition, this paper comprehensively considers and analyzes to meet the actual needs of users to build a multi-functional sports training system based on visual sensing. Finally, this paper designs a controlled experiment to evaluate the performance of the model constructed in this paper. The research results show that the model constructed in this paper has certain practical effects.
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