Machine Learning Seismic Wave Discrimination: Application to Earthquake Early Warning

@article{Li2018MachineLS,
  title={Machine Learning Seismic Wave Discrimination: Application to Earthquake Early Warning},
  author={Zefeng Li and Men‐Andrin Meier and Egill Hauksson and Zhongwen Zhan and Jennifer Andrews},
  journal={Geophysical Research Letters},
  year={2018},
  volume={45},
  pages={4773 - 4779}
}
Performance of earthquake early warning systems suffers from false alerts caused by local impulsive noise from natural or anthropogenic sources. To mitigate this problem, we train a generative adversarial network (GAN) to learn the characteristics of first‐arrival earthquake P waves, using 300,000 waveforms recorded in southern California and Japan. We apply the GAN critic as an automatic feature extractor and train a Random Forest classifier with about 700,000 earthquake and noise waveforms… 

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