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: 2,866 (including HTML, PDF, and XML)
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Total
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2,455
361
50
2,866
187
195
HTML: 2,455
PDF: 361
XML: 50
Total: 2,866
BibTeX: 187
EndNote: 195
Views and downloads (calculated since 06 Apr 2023)
Cumulative views and downloads
(calculated since 06 Apr 2023)
Total article views: 2,576 (including HTML, PDF, and XML)
HTML
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BibTeX
EndNote
2,165
361
50
2,576
182
190
HTML: 2,165
PDF: 361
XML: 50
Total: 2,576
BibTeX: 182
EndNote: 190
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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BibTeX
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290
0
0
290
5
5
HTML: 290
PDF: 0
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Total: 290
BibTeX: 5
EndNote: 5
Views and downloads (calculated since 06 Apr 2023)
Cumulative views and downloads
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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: 2,866 (including HTML, PDF, and XML)
Thereof 2,766 with geography defined
and 100 with unknown origin.
Total article views: 2,576 (including HTML, PDF, and XML)
Thereof 2,489 with geography defined
and 87 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...
