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...
Guardado en:
Autores principales: | Gregory C. Beroza, Margarita Segou, S. Mostafa Mousavi |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/60dc86c11f92451d91a938138bf66429 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Earthquake transformer—an attentive deep-learning model for simultaneous earthquake detection and phase picking
por: S. Mostafa Mousavi, et al.
Publicado: (2020) -
Forecasting the magnitude of the largest expected earthquake
por: Robert Shcherbakov, et al.
Publicado: (2019) -
Earthquake source characterization by machine learning algorithms applied to acoustic signals
por: Bernabe Gomez, et al.
Publicado: (2021) -
Forecasting influenza activity using machine-learned mobility map
por: Srinivasan Venkatramanan, et al.
Publicado: (2021) -
Next steps of quantum transport in Majorana nanowire devices
por: Hao Zhang, et al.
Publicado: (2019)