Earth Surface Dynamics
Earth Surface Dynamics
ESurf
Articles | Volume 9, issue 5
Articles | Volume 9, issue 5
https://doi.org/10.5194/esurf-9-1091-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esurf-9-1091-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 9, issue 5
Research article
 | 
03 Sep 2021
Research article |  | 03 Sep 2021

Inverse modeling of turbidity currents using an artificial neural network approach: verification for field application

Hajime Naruse and Kento Nakao

Viewed

Total article views: 3,200 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,230 899 71 3,200 97 130
  • HTML: 2,230
  • PDF: 899
  • XML: 71
  • Total: 3,200
  • BibTeX: 97
  • EndNote: 130
Views and downloads (calculated since 19 Nov 2020)
Cumulative views and downloads (calculated since 19 Nov 2020)

Viewed (geographical distribution)

Total article views: 3,200 (including HTML, PDF, and XML) Thereof 2,941 with geography defined and 259 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 27 Oct 2025
Download
Short summary
This paper proposes a method to reconstruct the hydraulic conditions of turbidity currents from turbidites. We investigated the validity and problems of this method in application to actual field datasets using artificial data. Once this method is established, it is expected that the method will elucidate the generation process of turbidity currents and will help to predict the geometry of resultant turbidites in deep-sea environments.
Read more
Share