A machine learning approach to enhance the SUPG stabilization method for advection-dominated differential problems
DOI10.3934/mine.2023032arXiv2111.00260OpenAlexW4285028908MaRDI QIDQ6195573
Tommaso Tassi, Alberto Zingaro, Luca Dedè
Publication date: 14 March 2024
Published in: Mathematics in Engineering (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2111.00260
finite element methodartificial neural networkspartial differential equationsmachine learningstabilization methodsstreamline upwind Petrov-Galerkin
Learning and adaptive systems in artificial intelligence (68T05) Finite element, Rayleigh-Ritz and Galerkin methods for boundary value problems involving PDEs (65N30) Finite element methods applied to problems in fluid mechanics (76M10) Finite element, Rayleigh-Ritz and Galerkin methods for initial value and initial-boundary value problems involving PDEs (65M60)
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