A comparative study based on AHP and fuzzy logic approaches for landslide susceptibility zoning using a GIS-based multi-criteria decision analysis
Author:
Funder
Ministerio de Ciencia e Innovación
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s41207-024-00552-w.pdf
Reference58 articles.
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2. Achour Y, Boumezbeur A, Hadji R et al (2017) Landslide susceptibility mapping using analytic hierarchy process and information value methods along a highway road section in Constantine, Algeria. Arab J Geosci 10:194. https://doi.org/10.1007/s12517-017-2980-6
3. Ahmadi R, El May M, Dlala M (2019) Ultimate slope design in open pit phosphate mine using geological and geomechanical analysis: case study of Jebel Jebbeus. Arab J Geosci 12:280. https://doi.org/10.1007/s12517-019-4333-0
4. Aleotti P, Chowdhury R (1999) Landslide hazard assessment: summary review and new perspectives. Bull Eng Geol Environ 58:21–44. https://doi.org/10.1007/s100640050066
5. Al-Najjar HAH, Pradhan B (2021) Spatial landslide susceptibility assessment using machine learning techniques assisted by additional data created with generative adversarial networks. Geosci Front 12:625–637. https://doi.org/10.1016/j.gsf.2020.09.002
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1. Landslide Susceptibility Mapping in North Tehran, Iran: Linear Regression, Neural Networks, and Fuzzy Logic Approaches;Geotechnical and Geological Engineering;2024-09-02
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