Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 6, Issue 2


Published
on

November 22, 2021


Pages

297-306


DOI

Article

Research on predictive control of students’ performance in PE classes based on the mathematical model of multiple linear regression equation

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Authors

Xin Liu Affiliation:
Hunan University of Science and Engineering, Institute of Physical Culture, YongZhou 425199, China
, Alaa Omar Khadidos Affiliation:
Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia
and Mohammed Yousuf Abo Keir Affiliation:
Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia


Abstract

Aiming to solve the problems in the traditional multiple regression analysis model for predicting college sports performance based on the principles of econometrics, a predictive model that combines genetic algorithm (GA), college sports performance evaluation and regression analysis is proposed. GA is used to conduct dynamic and supervised optimisation evaluation of college sports performance; on this basis, combined with regression analysis and GA's global optimisation capabilities, a complex nonlinear relationship between student sports performance and influencing factors is established; the student's performance is calculated based on the college sports performance. The results show that the method has high prediction accuracy and good stability.


Keywords

regression analysis, college sports performance, college sports, performance, prediction, 34A34


Citation

Liu, X., Khadidos, A. O., & Abo Keir, M. Y. (2021). Research on predictive control of students’ performance in PE classes based on the mathematical model of multiple linear regression equation. Applied Mathematics and Nonlinear Sciences, 6(2), 297–306. https://doi.org/10.2478/amns.2021.2.00058

Published by: Engineering Journals

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