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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....
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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MDPI
2023
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| 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 |