Machine learning and earthquake forecasting—next steps

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...

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Detalles Bibliográficos
Autores principales: Beroza, Gregory C., Segou, Margarita, Mostafa Mousavi, S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Comment
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8346575/
https://www.ncbi.nlm.nih.gov/pubmed/34362887
http://dx.doi.org/10.1038/s41467-021-24952-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8346575/
https://www.ncbi.nlm.nih.gov/pubmed/34362887
http://dx.doi.org/10.1038/s41467-021-24952-6

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