Pseudo-static slope stability analysis using explainable machine learning techniques
Author:
Funder
Prime Minister Research Fellowship from Ministry of Education, India
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11069-024-06839-z.pdf
Reference52 articles.
1. Alqadhi S, Mallick J, Alkahtani M, Ahmad I, Alqahtani D, Hang HT (2023) Developing a hybrid deep learning model with explainable artificial intelligence (XAI) for enhanced landslide susceptibility modeling and management. Nat Hazards. https://doi.org/10.1007/s11069-023-06357-4
2. Azmoon B, Biniyaz A, Liu Z, Sun Y (2021) Image-data-driven slope stability analysis for preventing landslides using deep learning. IEEE Access 9:150623–150636. https://doi.org/10.1109/ACCESS.2021.3123501
3. Baker R, Shukha R, Operstein V, Frydman S (2006) Stability charts for pseudo−static slope stability analysis. Soil Dynam Earthq Eng 26(9):813–823. https://doi.org/10.1016/j.soildyn.2006.01.023
4. Basha BM, Babu G (2011) Reliability based earthquake resistant design for internal stability of reinforced soil structures. Geotech Geol Eng 29:803–820. https://doi.org/10.1007/s10706-011-9418-9
5. Bergstra J, Bengio Y (2012) Random search for hyper-parameter optimization. J Mach Learn Res 13:281–305. https://doi.org/10.5555/2188385.2188395
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