Research on Classification of College Students’ Physical Fitness Test Scores Based on Neural Network

A healthy body enables a person to spend more time in everyday life, learning and work. Students’ body diathesis has long been a key issue in higher education institutions, and it is the final target to cultivate all-round talents. An integrated performance forecast model is presented in this paper. Firstly, PCA decreases the time and space of the model training by removing redundant information. Then, a PNN method was adopted to build a PNN forecast model, and then it was used in the experimental dataset to assess the model’s performance.At last, this paper uses the QFT model to forecast the synthetic performance of other years and compares the forecast results with those of humans. It is found that because of the influence of people’s involvement, the calculating standard of compound marks can not be uniform for a long time. Therefore, it is very important to forecast the synthetic marks using this model.