Performance assessment of the landslide susceptibility modelling using the support vector machine, radial basis function network, and weight of evidence models in the N'fis river basin, Morocco

Performance assessment of the landslide susceptibility modelling using the support vector machine, radial basis function network, and weight of evidence models in the N'fis river basin, Morocco

Abstract Landslides in mountainous areas are one of the most important natural hazards and potentially cause severe damage and loss of human life. In order to reduce this damage, it is essential to determine the potentially vulnerable sites. The objective of this study was to produce a landslide vul...

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Bibliographic Details
Main Authors: Hassan Ait Naceur, Hazem Ghassan Abdo, Brahim Igmoullan, Mustapha Namous, Hussein Almohamad, Ahmed Abdullah Al Dughairi, Motrih Al-Mutiry
Format: Article
Language:English
Published: SpringerOpen 2022-10-01
Series:Geoscience Letters
Subjects:
Landslide susceptibility
GIS
Weight of evidence (WoE)
Support vector machine (SVM)
Radial basis function network (RBFN)
Morocco
Online Access:https://doi.org/10.1186/s40562-022-00249-4

Internet

https://doi.org/10.1186/s40562-022-00249-4

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