Research Article
Prediction of Ultimate Bearing Capacity of Cohesionless Soils Using Soft Computing Techniques
Table 2
Performance evaluation of different models for training dataset.
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Performance index |
Meyerhof [2] |
Hansen [3] |
Vesic [4] | SVM* | GP* | Polykernel (C = 100; d = 2) | RBF kernel (C = 250; σ = 3) |
| R | 0.9307 | 0.9295 | 0.9408 | 0.9742 | 0.9977 | 0.9923 | E | 0.7387 | 0.6908 | 0.7208 | 0.9408 | 0.9948 | 0.9900 | RMSE (kPa) | 260.0015 | 282.8295 | 268.7726 | 123.7923 | 36.8280 | 65.0650 | MBE (kPa) | −78.3587 | −95.8701 | −103.2620 | −9.5919 | −3.5807 | −0.8618 | MARE | 19.6545 | 20.9268 | 25.6619 | 19.3968 | 1.8036 | 12.9030 |
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Present study.
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