Statistics Program, Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
Physical Science and Engineering (PSE) Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
Viewed
Since the preprint corresponding to this journal article was posted outside of Copernicus Publications, the preprint-related metrics are limited to HTML views.
Total article views: 3,666 (including HTML, PDF, and XML)
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3,152
446
68
3,666
207
221
HTML: 3,152
PDF: 446
XML: 68
Total: 3,666
BibTeX: 207
EndNote: 221
Views and downloads (calculated since 06 Apr 2023)
Cumulative views and downloads
(calculated since 06 Apr 2023)
Total article views: 3,376 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
2,862
446
68
3,376
202
216
HTML: 2,862
PDF: 446
XML: 68
Total: 3,376
BibTeX: 202
EndNote: 216
Views and downloads (calculated since 08 Mar 2024)
Cumulative views and downloads
(calculated since 08 Mar 2024)
Total article views: 290 (including HTML, PDF, and XML)
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290
0
0
290
5
5
HTML: 290
PDF: 0
XML: 0
Total: 290
BibTeX: 5
EndNote: 5
Views and downloads (calculated since 06 Apr 2023)
Cumulative views and downloads
(calculated since 06 Apr 2023)
Viewed (geographical distribution)
Since the preprint corresponding to this journal article was posted outside of Copernicus Publications, the preprint-related metrics are limited to HTML views.
Total article views: 3,666 (including HTML, PDF, and XML)
Thereof 3,527 with geography defined
and 139 with unknown origin.
Total article views: 3,376 (including HTML, PDF, and XML)
Thereof 3,250 with geography defined
and 126 with unknown origin.
Total article views: 290 (including HTML, PDF, and XML)
Thereof 277 with geography defined
and 13 with unknown origin.
We propose a modeling approach capable of recognizing slopes that may generate landslides, as well as how large these mass movements may be. This protocol is implemented, tested, and validated with data that change in both space and time via an Ensemble Neural Network architecture.
We propose a modeling approach capable of recognizing slopes that may generate landslides, as...
