Towards a deep learning approach for short-term data-driven spatiotemporal seismicity rate forecasting
Abstract Recent advances in earthquake monitoring have led to the development of methods for the automatic generation of high-resolution catalogues. These catalogues are created at considerably reduced processing times and contain significantly larger volumes of data concerning seismic activity comp...
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| Principais autores: | , , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
SpringerOpen
2025-11-01
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| coleção: | Earth, Planets and Space |
| Assuntos: | |
| Acesso em linha: | https://doi.org/10.1186/s40623-025-02241-6 |
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