Table 1 Statistical analysis of the experimental data.

From: Investigating a hybrid extreme learning machine coupled with Dingo Optimization Algorithm for modeling liquefaction triggering in sand-silt mixtures

Category

Statistics

Sigma c (Kp)

Dr (%)

FC (%)

Cu

D50 (mm)

W (J/m3)

Training samples

Xmax

400

93

60

28.120

0.260

12,230

Xav

103.470

62.807

14.710

8.101

0.165

2372.130

Xmin

14.130

9.380

0

1.520

0.029

385

Xst.d

83.872

15.641

17.544

9.655

0.056

2156.920

Ssks

2.531

− 0.657

0.997

1.349

− 0.403

2.285

Xmed

100

64.595

5

2.270

0.15

1705.450

Testing Samples

Xmax

400

88.020

60

28.120

0.26

15,000

Xav

92.13

60.505

13.627

6.277

0.155

2075.800

Xmin

28.400

25

0

1.520

0.029

398.200

Xst.d

75.647

13.078

17.239

8.293

0.049

2545.110

Ssks

3.129

− 0.572

0.989

2.004

0.067

3.452

Xmed

82.740

62

5

2.270

0.15

1317

Overall samples

Xmax

400

93

60

28.120

0.26

15,000

Xav

100.060

62.114

14.384

7.552

0.162

2283.02

Xmin

14.130

9.380

0

1.520

0.029

385

Xst.d

81.389

14.909

17.4

9.275

0.054

2275.520

Ssks

2.6837

− 0.609

0.996

1.515

− 0.268

2.744

Xmed

100

62.700

5

2.27

0.15

1609