Prediction and optimization of individual skill development patterns in physical education based on big data analysis

Abstract

This paper proposes a data-based gray preprocessing neural network optimization model based on the principle of the BP neural network model and its optimization method. SPSS statistical software was used for statistical analysis to compare the student physical education test data of S college students from 2019 to 2023. The GA-BP optimization prediction model is applied to generate and process the raw data of 5-year sports tests to find the law of systematic changes and generate the data sequence with strong regularity so as to predict the condition of the future development trend of things. The results show that the measured and actual numbers have a high rate of conformity, and the maximum error is 0.67%, which is high accuracy. The overall speed and strength of boys and girls in sports is on the rise. The overall endurance level of boys is increasing while the overall endurance level of girls is decreasing. In the future, endurance training should be strengthened as a way to improve the continuing trend of low endurance quality among students.

Keywords

• bp neural network
• ga-bp optimization prediction model
• sports test
• gray preprocessing
• 00a35