Development of machine learning surrogate models for slope stability prediction using AI techniques: a case study of the Meizhou landslide

Abstract Rainfall-induced landslides present a critical global geohazard, necessitating the development of robust, rapid tools for slope stability evaluation. This study proposes a hybrid framework that integrates numerical modeling with machine learning (ML) regression to predict the Factor of Safe...

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Autors principals:	Muhammad Israr Khan, Jianbo Fei, Xiangsheng Chen, Muhammad Hamza
Format:	Artigo
Idioma:	Inglês
Publicat:	Nature Portfolio 2026-01-01
Col·lecció:	Scientific Reports
Matèries:	Slope stability prediction Machine learning regression XGBoost Surrogate modeling Rainfall-induced landslide Factor of safety (FoS)
Accés en línia:	https://doi.org/10.1038/s41598-025-33324-9
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