A deep learning physics-informed neural network (PINN) for predicting drilled shaft axial capacity

Accurately estimating the axial capacity of drilled shafts remains a persistent challenge in geotechnical engineering, as evidenced by significant discrepancies between measured load-test results and theoretical predictions. To bridge this gap, a novel Deep Learning–Physics-Informed Neural Network (...

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Bibliographic Details
Main Author: M.E. Al-Atroush
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:Applied Computing and Geosciences
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S259019742500028X
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