Machine learning reveals cyclic changes in seismic source spectra in Geysers geothermal field

The earthquake rupture process comprises complex interactions of stress, fracture, and frictional properties. New machine learning methods demonstrate great potential to reveal patterns in time-dependent spectral properties of seismic signals and enable identification of changes in faulting processe...

Descripción completa

Detalles Bibliográficos
Autores principales: Holtzman, Benjamin K., Paté, Arthur, Paisley, John, Waldhauser, Felix, Repetto, Douglas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2018
Materias:
Research Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5966224/
https://www.ncbi.nlm.nih.gov/pubmed/29806015
http://dx.doi.org/10.1126/sciadv.aao2929

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5966224/
https://www.ncbi.nlm.nih.gov/pubmed/29806015
http://dx.doi.org/10.1126/sciadv.aao2929

Ejemplares similares