# A two-stage physics-informed neural network method based on conserved quantities and applications in localized wave solutions

@inproceedings{Lin2021ATP, title={A two-stage physics-informed neural network method based on conserved quantities and applications in localized wave solutions}, author={Shuning Lin and Yong Chen}, year={2021} }

With the advantages of fast calculating speed and high precision, the physics-informed neural network method opens up a new approach for numerically solving nonlinear partial differential equations. Based on conserved quantities, we devise a two-stage PINN method which is tailored to the nature of equations by introducing features of physical systems into neural networks. Its remarkable advantage lies in that it can impose physical constraints from a global perspective. In stage one, the… Expand

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