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

Xin Liu
Xin Liu
, 
Alaa Omar Khadidos
Alaa Omar Khadidos
 y 
Mohammed Yousuf Abo Keir
Mohammed Yousuf Abo Keir
   | 22 nov 2021
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Publicado en línea: 22 nov 2021
Páginas: 297 - 306
Recibido: 17 jun 2021
Aceptado: 24 sept 2021
DOI: https://doi.org/10.2478/amns.2021.2.00058
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© 2021 Xin Liu et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

Forecast model algorithm flow chart.
Forecast model algorithm flow chart.

Fig. 2

Schematic diagram of random traversal sampling.
Schematic diagram of random traversal sampling.

Fig. 3

Schematic diagram of single-point crossover operation.
Schematic diagram of single-point crossover operation.

Fig. 4

Schematic diagrams of the relationship between the number of college sports performance levels and the goodness of fit R2.
Schematic diagrams of the relationship between the number of college sports performance levels and the goodness of fit R2.

List of dummy variable settings for college sports performance grades.

Category K 1 2 3 . . . k
Virtual variable D1 0 1 1 1 1
D2 1 0 1 1 1
D3 1 1 0 1 1
. . . . . . . . . . . . . . . . . .
D (k−1) 1 1 1 0 1

List of the classification results of the merits of each school (region) and college sports performance.

Classmate code Performance prediction
Actual Prediction Strength ranking
A 98.55 98 1
B 98 98 1
C 98 98 1
D 98 98 1
E 97.25 97 2
F 97.11 97 2
G 97.1 97 2
H 96.12 96 3
I 92.12 92 4
J 92 92 4
K 90 90 5
L 90 90 5
M 89.11 89 6
N 89.12 89 6
O 87.12 87 7
P 86 86 8

Summary of the regression results of the share of outstanding and excellent results in college sports from 2014 to 2018

Regression results of performance share Regression results of outstanding performance share
Coefficient t Coefficient t
log (POP) 0.700580484 4.046 0.415217178 3.612307
log (PGDP) 0.00492357 3.8 0.507549691 1.092639
Home 0.720660842 1.656 0.950142728 3.393209
Mt-1 0.935333311 0.9 0.733616507 4.407553
β0 0.819858339 0.645 0.949132464 2.307292
D1 0.233461872 1.489 0.861656496 0.10588
D2 0.522969528 4.718 0.159542912 1.948906
D3 0.887297088 3.593 0.108918231 3.609763
D4 0.673300591 4.348 0.916780756 1.823459
D5 0.681120134 1.667 0.871739745 1.593532
D6 0.767696616 2.757 0.6677149 1.354243
Statistical test R2 = 0.9544 F = 491.43223 R2 = 0.9254 F = 444.43223

Summary of the results of the two models’ prediction statistical indicators.

Model RMSE MAPE MAE PEA
Grades FCM 7.123 0.5446 4.789 0.954
GA 6.785 0.5214 3.256 0.957
Excellent results FCM 3.456 0.4851 2.0657 0.925
GA 3.278 0.4712 2.2145 0.952
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Life Sciences, other, Mathematics, Applied Mathematics, General Mathematics, Physics
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