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: 3,998 (including HTML, PDF, and XML)
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3,329
583
86
3,998
223
236
HTML: 3,329
PDF: 583
XML: 86
Total: 3,998
BibTeX: 223
EndNote: 236
Views and downloads (calculated since 06 Apr 2023)
Cumulative views and downloads
(calculated since 06 Apr 2023)
Total article views: 3,708 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
3,039
583
86
3,708
218
231
HTML: 3,039
PDF: 583
XML: 86
Total: 3,708
BibTeX: 218
EndNote: 231
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: 3,998 (including HTML, PDF, and XML)
Thereof 3,845 with geography defined
and 153 with unknown origin.
Total article views: 3,708 (including HTML, PDF, and XML)
Thereof 3,568 with geography defined
and 140 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...
