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From
Predicting the Bearing Capacity of a Shallow Foundation Using Artificial Neural Networks with MATLAB: The Case of the Daraal Peulh Site (Senegal)
Hamed FALL, Déthié SARR, Lamine BAR, Abdou Aziz WELLE
American Journal of Civil Engineering and Architecture
.
2026
, 14(4), 176-188 doi:10.12691/ajcea-14-4-5
Table 1. Results of soil identification tests
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Table 2. Results of direct shear tests
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Table 3. (φ, C) pairs from direct shear tests at the DaraalPeulh site
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Table 4. Excerpt from the database used for training
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Table 5. Validation on Independent Data
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Table 6. Final performance metrics and distribution of observations for the training, validation, and test phases
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Table 7. Evolution of the mixed-model training indicators (Training State)
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Table 8. Input Normalization Parameters
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Table 9. Network weights and biases (12 hidden neurons, 1 output)
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