Prediction of College Students'Physical Test Scores Based on Radial Basis Function Neural Network
The scores of physical fitness tests for college students are important indicators for e-valuating their physical health.Scientific and effective prediction and analysis of physical fitness test scores serve as the basis for other research.In this paper,a prediction method for college student physi-cal fitness test scores based on Radial Basis Function Neural Networks(RBFNN)is proposed.The RBFNN is used to predict and analyze the physical fitness test data of students of a certain university in 2022,and the classification prediction results are compared with those of Back Propagation Neural Net-work(BPNN),Support Vector Machines(SVM),and other methods.The experimental results dem-onstrate that the proposed prediction model based on RBFNN exhibits high prediction accuracy and good generalization performance for college student physical fitness test scores.It provides a scientifically ef-fective analysis method for physical education teachers'teaching and researchers'subsequent studies.
Radial Basis Function Neural Networksphysical health testgrade prediction
万方数据
维普
