A study on small magnitude seismic phase identification using 1D deep residual neural network

A study on small magnitude seismic phase identification using 1D deep residual neural network

Reliable seismic phase identification is often challenging especially in the circumstances of low-magnitude events or poor signal-to-noise ratio. With improved seismometers and better global coverage, a sharp increase in the volume of recorded seismic data has been achieved. This makes handling seis...

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Bibliographic Details
Main Authors: Wei Li, Megha Chakraborty, Yu Sha, Kai Zhou, Johannes Faber, Georg Rümpker, Horst Stöcker, Nishtha Srivastava
Format: Article
Language:English
Published: KeAi Communications Co. Ltd. 2022-12-01
Series:Artificial Intelligence in Geosciences
Subjects:
Deep learning
Residual neural network
Earthquake detection
Seismic phase identification
Online Access:http://www.sciencedirect.com/science/article/pii/S2666544122000284

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http://www.sciencedirect.com/science/article/pii/S2666544122000284

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