Solving groundwater flow equation using physics-informed neural networks

DOI10.1016/J.CAMWA.2023.05.036OpenAlexW4381888481MaRDI QIDQ6176691

Vincenzo Schiano Di Cola, Fabio Giampaolo, Salvatore Cuomo, Stefano Izzo, Mariapia De Rosa

Publication date: 23 August 2023

Published in: Computers \& Mathematics with Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.camwa.2023.05.036

zbMATH Keywords

unsteady flowPINNphysics-informed machine learningscientific machine learning

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Learning and adaptive systems in artificial intelligence (68T05) Computation of special functions and constants, construction of tables (65D20) Finite difference methods for boundary value problems involving PDEs (65N06) Approximation by other special function classes (41A30)

Cites Work

• Unnamed Item
• On the near optimality of the stochastic approximation of smooth functions by neural networks
• Remarks on the numerical approximation of Dirac delta functions
• Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
• Neural‐network‐based approximations for solving partial differential equations
• The Modern Mathematics of Deep Learning

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