An integrated approach of hybrid ensemble machine learning-based efficient seismic slope fragility assessment and GIS mapping

Abstract Seismic slope failures are difficult to predict due to the probabilistic nature of soil properties and seismic loads. Additionally, high-fidelity simulation-based fragility assessment methods for soil slopes require substantial computational resources, making it time-consuming to link these...

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Bibliografiske detaljer

Principais autores:	Rahman Md Mostafizur, Chaeyeon Go, Shinyoung Kwag, Seunghyun Eem, Daegi Hahm
Format:	Artigo
Sprog:	Inglês
Udgivet:	Nature Portfolio 2026-02-01
Serier:	Scientific Reports
Fag:	Seismic slope failure Fragility analysis Machine learning (ML) Hybrid ensemble method (HEM) Geographic information system (GIS)
Online adgang:	https://doi.org/10.1038/s41598-026-38171-w
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