Table 7 Efficiency criteria for various models.

From: Axial strength prediction of FRP reinforced concrete columns under concentric and eccentric loading using machine learning models

Method

ANN

MLR

GMDH

GEP

MAE_train

118.13

433.44

153.42

195.70

MAE_test

130.13

460.41

208.32

241.43

MAE- All data

121.54

440.89

169.94

209.010

RMSE_train

195.51

610.93

209.34

280.73

RMSE_test

211.45

615.02

296.85

368.67

RMSE- All data

206.61

611.59

239.07

309.417

MAPE_train

8.59

51.95

16.1

16.53

MAPE_test

11.05

52.68

19.2

23.23

MAPE- All data

9.32

52.41

17.01

18.505

\(R^{2} - train\)

0.981

0.754

0.973

0.949

\(R^{2} - test\)

0.960

0.810

0.949

0.934

\(R^{2}\)- All data

0.974

0.775

0.966

0.942

Average of errors

9.32

59.22

17.01

18.51

Standard deviation of errors

10.22

166.38

31.05

41.55

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