Seismic Features Predict Ground Motions During Repeating Caldera Collapse Sequence

Seismic Features Predict Ground Motions During Repeating Caldera Collapse Sequence

Abstract Applying machine learning to continuous acoustic emissions, signals previously deemed noise, from laboratory faults and slowly slipping subduction‐zone faults, demonstrates hidden signatures are emitted that describe physical details, including fault displacement and friction. However, no e...

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Bibliographic Details
Main Authors: Christopher W. Johnson, Paul A. Johnson
Format: Article
Language:English
Published: Wiley 2024-06-01
Series:Geophysical Research Letters
Subjects:
machine learning
seismic
GNSS
ground motions
predicting fault time to failure
Online Access:https://doi.org/10.1029/2024GL108288

Internet

https://doi.org/10.1029/2024GL108288

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