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Predicting fault slip via transfer learning
Data-driven machine-learning for predicting instantaneous and future fault-slip in laboratory experiments has recently progressed markedly, primarily due to large training data sets. In Earth however, earthquake interevent times range from 10’s-100’s of years and geophysical data typically exist for...
Autores principales: | Wang, Kun, Johnson, Christopher W., Bennett, Kane C., Johnson, Paul A. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8677738/ https://www.ncbi.nlm.nih.gov/pubmed/34916491 http://dx.doi.org/10.1038/s41467-021-27553-5 |
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