Inverse analysis for estimating geotechnical parameters using physics-informed neural networks

Physics-informed neural networks (PINNs) have been proposed for incorporating physical laws into deep learning. PINNs can output solutions that satisfy physical laws by introducing information, such as partial differential equations (PDEs), boundary conditions, and initial conditions, into the loss...

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Bibliographic Details
Main Authors: Shinichi Ito, Ryusei Fukunaga, Kazunari Sako
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Soils and Foundations
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S0038080624001112
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