Articles | Volume 21, issue 5
https://doi.org/10.5194/nhess-21-1667-2021
https://doi.org/10.5194/nhess-21-1667-2021
Research article
 | 
31 May 2021
Research article |  | 31 May 2021

Reconstruction of flow conditions from 2004 Indian Ocean tsunami deposits at the Phra Thong island using a deep neural network inverse model

Rimali Mitra, Hajime Naruse, and Shigehiro Fujino

Viewed

Total article views: 2,072 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,371 649 52 2,072 65 60
  • HTML: 1,371
  • PDF: 649
  • XML: 52
  • Total: 2,072
  • BibTeX: 65
  • EndNote: 60
Views and downloads (calculated since 16 Nov 2020)
Cumulative views and downloads (calculated since 16 Nov 2020)

Viewed (geographical distribution)

Total article views: 2,072 (including HTML, PDF, and XML) Thereof 1,970 with geography defined and 102 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 12 Nov 2024
Download
Short summary
A case study on the 2004 Indian Ocean tsunami was conducted at the Phra Thong island, Thailand, using a deep neural network (DNN) inverse model. The model estimated tsunami characteristics from the deposits at Phra Thong island. The uncertainty quantification of the result was evaluated. The predicted flow conditions and the depositional characteristics were compared with the reported observed values. This DNN model can serve as an essential tool for tsunami hazard mitigation at coastal cities.
Altmetrics
Final-revised paper
Preprint