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Near-surface velocity estimation using shear-waves and deep-learning with a U…
Estimation of good velocity models under complex near-surface conditions remains a topic of ongoing research. We propose to predict near-surface velocity profiles from surface-waves transformed to phase velocity-frequency panels in a data-driven manner using deep neural networks. This is a different approach from many recent works that attempt to estimate velocity from directly reflected body w…
- Edisi
- Vol.3, December 2022
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 16 hlm PDF, 12.932 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Near-surface velocity inversion from Rayleigh wave dispersion curves based on…
The utilization of urban underground space in a smart city requires an accurate understanding of the underground structure. As an effective technique, Rayleigh wave exploration can accurately obtain information on the subsurface. In particular, Rayleigh wave dispersion curves can be used to determine the near-surface shear-wave velocity structure. This is a typical multiparameter, high-dimensio…
- Edisi
- Vol.2, December 2021
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 12 hlm PDF, 2.687 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
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