Landslide susceptibility assessment of South Korea using stacking ensemble machine learning

Landslide susceptibility assessment of South Korea using stacking ensemble machine learning

Abstract Background Landslide susceptibility assessment (LSA) is a crucial indicator of landslide hazards, and its accuracy is improving with the development of artificial intelligence (AI) technology. However, the AI algorithms are inconsistent across regions and strongly dependent on input variabl...

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Bibliographic Details
Main Authors: Seung-Min Lee, Seung-Jae Lee
Format: Article
Language:English
Published: SpringerOpen 2024-02-01
Series:Geoenvironmental Disasters
Subjects:
Landslide
Susceptibility model
Stacking ensemble
Machine learning
Online Access:https://doi.org/10.1186/s40677-024-00271-y

Internet

https://doi.org/10.1186/s40677-024-00271-y

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