Identification of partial differential equations from noisy data with integrated knowledge discovery and embedding using evolutionary neural networks
Identification of underlying partial differential equations (PDEs) for complex systems remains a formidable challenge. In the present study, a robust PDE identification method is proposed, demonstrating the ability to extract accurate governing equations under noisy conditions without prior knowledg...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-03-01
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| Series: | Theoretical and Applied Mechanics Letters |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2095034924000229 |