Physics-informed deep learning for structural dynamics under moving load
Physics-informed deep learning has emerged as a promising approach that incorporates physical constraints into the model, reduces the amount of data required, and demonstrates robustness and potential in dealing with limited datasets for a variety of studies. However, several key challenges still ex...
| Main Authors: | , , , |
|---|---|
| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/182853 |