Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 16, issue 17
Articles | Volume 16, issue 17
https://doi.org/10.5194/gmd-16-5265-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-5265-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 16, issue 17
Model description paper
 | 
14 Sep 2023
Model description paper |  | 14 Sep 2023

AutoQS v1: automatic parametrization of QuickSampling based on training images analysis

Mathieu Gravey and Grégoire Mariethoz

Viewed

Total article views: 1,345 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,004 286 55 1,345 39 34
  • HTML: 1,004
  • PDF: 286
  • XML: 55
  • Total: 1,345
  • BibTeX: 39
  • EndNote: 34
Views and downloads (calculated since 17 Oct 2022)
Cumulative views and downloads (calculated since 17 Oct 2022)

Viewed (geographical distribution)

Total article views: 1,345 (including HTML, PDF, and XML) Thereof 1,259 with geography defined and 86 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 07 May 2024
Download
Short summary
Multiple‐point geostatistics are widely used to simulate complex spatial structures based on a training image. The use of these methods relies on the possibility of finding optimal training images and parametrization of the simulation algorithms. Here, we propose finding an optimal set of parameters using only the training image as input. The main advantage of our approach is to remove the risk of overfitting an objective function.
Read more