Research Article
Prediction of Ultimate Bearing Capacity of Cohesionless Soils Using Soft Computing Techniques
Table 4
Performance evaluation of different models for testing dataset.
| Performance index |
Meyerhof [2] |
Hansen [3] |
Vesic [4] |
ANN [5] |
FIS [5] | SVM* | GP* | Polykernel (C = 100; d = 2) | RBF Kernel (C = 250; σ = 3) |
| R | 0.9410 | 0.9366 | 0.9456 | 0.9951 | 0.9899 | 0.9775 | 0.9806 | 0.9972 | E | 0.7863 | 0.7583 | 0.7321 | 0.9942 | 0.9858 | 0.9541 | 0.9504 | 0.9965 | RMSE (kPa) | 269.947 | 287.099 | 302.269 | 62.620 | 98.002 | 125.087 | 130.102 | 44.967 | MBE (kPa) | −127.724 | −139.611 | −158.552 | −21.89 | 13.92 | 34.11 | 4.75 | 4.019 | MARE | 22.0679 | 20.0152 | 28.515 | 13.314 | 19.456 | 14.7278 | 9.4528 | 7.6817 |
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Present study.
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