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Physics-Informed Neural Networks for High-Frequency and Multi-Scale Problems using Transfer Learning
We proposed using transfer learning to boost the robustness and convergence of training PINN, starting training from low-frequency problems and gradually approaching high-frequency problems.
Wave based damage detection in solid structures using artificial neural networks
Although the training of the model is still time consuming, the proposed new method has an enormous potential to become a new crack detection or structural health monitoring approach within the conventional monitoring methods.
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