Articles | Volume 64
https://doi.org/10.5194/adgeo-64-23-2024
https://doi.org/10.5194/adgeo-64-23-2024
22 Aug 2024
 | 22 Aug 2024

An Efficient Surrogate-based Multi-objective Optimisation Framework with Novel Sampling Strategy for Sustainable Island Groundwater Management

Weijiang Yu, Domenico Baù, Alex S. Mayer, and Mohammadali Geranmehr

Viewed

Total article views: 153 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
125 17 11 153 5 5
  • HTML: 125
  • PDF: 17
  • XML: 11
  • Total: 153
  • BibTeX: 5
  • EndNote: 5
Views and downloads (calculated since 22 Aug 2024)
Cumulative views and downloads (calculated since 22 Aug 2024)

Viewed (geographical distribution)

Total article views: 145 (including HTML, PDF, and XML) Thereof 145 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 03 Oct 2024
Download
Short summary
This study proposes an offline machine-learning (ML) algorithm that ranks candidate training points by scoring them based on their distance to the closest training point and on the local gradient of the surrogate estimate and then choosing the highest-rank point. The effectiveness of this method is confirmed in developing surrogates to solve a two-objective groundwater pumping optimization problem formulated on a three-dimensional island aquifer.