Deep Galerkin Method for Burgers’ Equation: A Comparative Study with Exact Solutions

Authors

  • Mustapha Bouallala "Cadi Ayyad University, UCA, Polydisciplinary Faculty of Safi, Modeling and Combinatorics Laboratory, Department of Mathematics and Computer Science B.P. 4162, Marrakesh, Morocco" & "Laboratory MSDTE, Hassan 1 University, 26000 Settat, Morocco" Author
  • Lakbir Essafi Laboratory MSDTE, Hassan 1 University, 26000 Settat, Morocco Author

DOI:

https://doi.org/10.65904/3083-3590.2025.01.03

Keywords:

Deep Galerkin Method (DGM), Burgers Equation, Physics-Informed Neural Networks (PINNs), Nonlinear Partial Differential Equations, Mesh-Free Methods, AMS MSC: 68T07, 35Q35, 68T07, 35-XX, 65M75

Abstract

This study evaluates the performance of the Deep Galerkin Method (DGM) for solving the Burgers equation in both one and two spatial dimensions. Through extensive numerical experiments, we show that DGM accurately reproduces the exact analytical solutions, effectively capturing the dynamics of viscous shock waves with errors below . The method demonstrates fast convergence, inherent geometric flexibility, and avoids the limitations of traditional mesh-based schemes, positioning DGM as a robust and efficient mesh-free approach for solving nonlinear partial differential equations.

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Published

2025-11-02

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