Phase Association
Links individual arrival times picked at different stations to a common origin. It is a critical step in earthquake monitoring.
Used ML Approaches:
Artificial Neural Networks
Used Neural Networks:
GRU
TCN
Used Learning Procedures:
Unsupervised Learning
Supervised Learning
References:
McBrearty, I. W., Gomberg, J., Delorey, A. A., & Johnson, P. A. (2019). Earthquake arrival association with backprojection and graph theory. Bulletin of the Seismological Society of America, 109(6), 2510-2531.
McBrearty, I. W., Delorey, A. A., & Johnson, P. A. (2019). Pairwise association of seismic arrivals with convolutional neural networks. Seismological Research Letters, 90(2A), 503-509.
Ross, Z. E., Yue, Y., Meier, M. A., Hauksson, E., & Heaton, T. H. (2019). PhaseLink: A deep learning approach to seismic phase association. Journal of Geophysical Research: Solid Earth, 124(1), 856-869.
Dickey, J., Borghetti, B., Junek, W., & Martin, R. (2020). Beyond correlation: A path‐invariant measure for seismogram similarity. Seismological Research Letters, 91(1), 356-369.
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