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Affine transformations accelerate the training of physics-informed neural networks of a one-dimensional consolidation problem
Physics-informed neural networks (PINNs) leverage data and knowledge about a problem. They provide a nonnumerical pathway to solving partial differential equations by expressing the field solution as an artificial neural network. This approach has been applied successfully to various types of differ...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10511457/ https://www.ncbi.nlm.nih.gov/pubmed/37730743 http://dx.doi.org/10.1038/s41598-023-42141-x |