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Physics-informed neural networks for high-resolution weather reconstruction from sparse weather stations.

Álvaro Moreno SotoAlejandro CervantesManuel Soler
Published in: Open research Europe (2024)
The effect of time and spatial resolution over the capability of the PINN to accurately reconstruct fluid phenomena is thoroughly discussed through a parametric study, concluding that a proper tuning of the neural network's loss function during training is of utmost importance.
Keyphrases
  • neural network
  • high resolution
  • mass spectrometry
  • tandem mass spectrometry