Machine learning and earthquake forecasting—next steps

Beroza, Gregory C.; Segou, M.; Mostafa Mousavi, S.. 2021 Machine learning and earthquake forecasting—next steps. Nature Communications, 12 (1), 4761. https://doi.org/10.1038/s41467-021-24952-6

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Official URL: http://dx.doi.org/10.1038/s41467-021-24952-6

Abstract/Summary

A new generation of earthquake catalogs developed through supervised machine-learning illuminates earthquake activity with unprecedented detail. Application of unsupervised machine learning to analyze the more complete expression of seismicity in these catalogs may be the fastest route to improving earthquake forecasting.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1038/s41467-021-24952-6
ISSN:	2041-1723
Date made live:	15 Oct 2021 10:37 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/531249

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1038/s41467-021-24952-6

ISSN:

2041-1723

Date made live:

15 Oct 2021 10:37 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/531249