Cargando…
A neural network based global traveltime function (GlobeNN)
Global traveltime modeling is an essential component of modern seismological studies with a whole gamut of applications ranging from earthquake source localization to seismic velocity inversion. Emerging acquisition technologies like distributed acoustic sensing (DAS) promise a new era of seismologi...
Autores principales: | Taufik, Mohammad H., Waheed, Umair bin, Alkhalifah, Tariq A. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10156740/ https://www.ncbi.nlm.nih.gov/pubmed/37137918 http://dx.doi.org/10.1038/s41598-023-33203-1 |
Ejemplares similares
-
Sensitivity Kernels of PP Precursor Traveltimes and Their Limitations for Imaging Topography of Discontinuities
por: Koroni, Maria, et al.
Publicado: (2019) -
Adjoint traveltime tomography unravels a scenario of horizontal mantle flow beneath the North China craton
por: Dong, Xingpeng, et al.
Publicado: (2021) -
Arrival times by Recurrent Neural Network for induced seismic events from a permanent network
por: Kolar, Petr, et al.
Publicado: (2023) -
ExplaiNN: interpretable and transparent neural networks for genomics
por: Novakovsky, Gherman, et al.
Publicado: (2023) -
Trauma of the globe: State of art in global and in China
por: Chen, Zhuo, et al.
Publicado: (2016)