A Second-Order Network Structure Based on Gradient-Enhanced Physics-Informed Neural Networks for Solving Parabolic Partial Differential Equations

Physics-informed neural networks (PINNs) are effective for solving partial differential equations (PDEs). This method of embedding partial differential equations and their initial boundary conditions into the loss functions of neural networks has successfully solved forward and inverse PDE problems....

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Detalles Bibliográficos
Autores principales: Sun, Kuo, Feng, Xinlong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10137436/
https://www.ncbi.nlm.nih.gov/pubmed/37190465
http://dx.doi.org/10.3390/e25040674

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10137436/
https://www.ncbi.nlm.nih.gov/pubmed/37190465
http://dx.doi.org/10.3390/e25040674

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