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Lessons learned from training an MLP model using layered feature sets for estimating pile bearing capacity

Machine Learning and Data Science in Geotechnics (2026) 2 (1): 122–134.

https://doi.org/10.1108/MLAG-12-2025-0022

Published: 11 May 2026

..., motivating data-driven approaches that better capture soil and geometry variability. Design/methodology/approach A database of 546 axial load tests is used to evaluate 12 feature representations ranging from geometry-only inputs to averaged soil descriptors and layered soil profiles sampled along...

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