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1. Predicting geological interfaces using stacking ensemble learning with multi-scale features.

2. Evaluation of design methods for side-resistance-only rock-socketed piles.

3. Hierarchical Bayesian model for predicting small-strain stiffness of sand.

4. Data-centric quasi-site-specific prediction for compressibility of clays.

5. Intelligent computing for modeling axial capacity of pile foundations.

6. Analytical prediction of ground movements due to circular shaft construction in clayey soils.

7. Prediction of ground-borne vibrations induced by impact pile driving: experimental validation of an equivalent linear approach.

8. Prediction of driven pile resistances in shales considering weathering and time effects.

9. Allocating transmissivities from constant head tests for the development of DFN models.

10. A physics-based approach for predicting time-dependent progression length of backward erosion piping.

11. Improvement of side resistance prediction for pile foundation using construction information.

12. Mapping soil nail loads using Federal Highway Administration (FHWA) simplified models and artificial neural network technique.

13. Reducing uncertainties and improving sand soil-water retention curve (SWRC) predictions for hazard screening analyses.

14. Meander migration: the observation method.

15. Implementation of the tangent modulus – vertical stress (Et–σv) model for flexible pavements analysis.