دورية أكاديمية
Machine Learning Predicts Earthquakes in the Continuum Model of a Rate‐And‐State Fault With Frictional Heterogeneities
| العنوان: | Machine Learning Predicts Earthquakes in the Continuum Model of a Rate‐And‐State Fault With Frictional Heterogeneities |
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| المؤلفون: | Reiju Norisugi, Yoshihiro Kaneko, Bertrand Rouet‐Leduc |
| المصدر: | Geophysical Research Letters, Vol 51, Iss 9, Pp n/a-n/a (2024) |
| بيانات النشر: | Wiley, 2024. |
| سنة النشر: | 2024 |
| المجموعة: | LCC:Geophysics. Cosmic physics |
| مصطلحات موضوعية: | machine learning, earthquake predictability, earthquake cycle simulations, foreshocks, network representation, Geophysics. Cosmic physics, QC801-809 |
| الوصف: | Abstract Machine learning (ML) has been used to study the predictability of laboratory earthquakes. However, the question remains whether or not this approach can be applied in a tectonic setting where one may have to rely on sparse earthquake catalogs, and where important timescales vary by orders of magnitude. Here, we apply ML to a synthetic seismicity catalog, generated by continuum models of a rate‐and‐state fault with frictional heterogeneities, which contains foreshocks, mainshocks, and aftershocks that nucleate in a similar manner. We develop a network representation of the seismicity catalog to calculate input features and find that the trained ML model can predict the time‐to‐mainshock with great accuracy, from the scale of decades to minutes. Our results offer clues as to why ML can predict laboratory earthquakes and how the developed approach could be applied to more complex problems where multiple timescales are at play. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1944-8007 0094-8276 |
| Relation: | https://doaj.org/toc/0094-8276; https://doaj.org/toc/1944-8007 |
| DOI: | 10.1029/2024GL108655 |
| URL الوصول: | https://doaj.org/article/5e5a273ceea94dcc83238d1100f61b3b |
| رقم الأكسشن: | edsdoj.5e5a273ceea94dcc83238d1100f61b3b |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 19448007 00948276 |
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| DOI: | 10.1029/2024GL108655 |