Prediction and Analysis of the Physical Test Scores Based on BP Neural Network and Principal Component Analysis Algorithm

Abstract

College students’ physical fitness test can comprehensively evaluate students’ physical health level from many aspects such as students’ body shape, quality, function, and sports ability. Through the analysis and prediction of college students’ physical fitness test results, it can be used to understand the actual physical quality of college students, formulate the evaluation standard of students’ physical health level, and assist physical education teachers to formulate reasonable teaching plans. For students with different physical quality, different training plans can be formulated to improve their actual physical quality. Aiming at this background, this paper puts forward a method based on BP neural network and principal component analysis algorithm of college students test score prediction algorithm, the BP neural network, and principal component analysis of machine learning algorithm successfully applied to physical test comprehensive performance prediction, implements the college students test transcript accurate prediction, and can effectively assist PE teachers to develop reasonable teaching plan. For students with different physical quality, different training plans can be formulated to improve their actual physical quality.