Early forecasting of tsunami inundation from tsunami and geodetic observation data with convolutional neural networks
Rapid and accurate hazard prediction is important for prompt evacuation and casualty reduction during natural disasters. Here, the authors present an AI-enabled tsunami forecasting approach, which provided rapid and accurate early warnings.
Saved in:
Main Authors: | Fumiyasu Makinoshima, Yusuke Oishi, Takashi Yamazaki, Takashi Furumura, Fumihiko Imamura |
---|---|
Format: | article |
Language: | EN |
Published: |
Nature Portfolio
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/b2dbf73069984e17b4e1bde9bf7038c0 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Probabilistic tsunami forecasting for early warning
by: J. Selva, et al.
Published: (2021) -
Tsunami Squares: Earthquake driven inundation mapping and validation by comparison to the Regional Ocean Modeling System
by: David P. Grzan, et al.
Published: (2021) -
Reflections on the Tsunami
by: Imam Zaid Shakir
Published: (2005) - Journal of earthquake and tsunami
-
Highly variable recurrence of tsunamis in the 7,400 years before the 2004 Indian Ocean tsunami
by: Charles M. Rubin, et al.
Published: (2017)