Evaluation of highway collapse hazard susceptibility based on the coupling of information value model and multiple machine learning models

Collapse hazards are among the most common geological hazards and pose severe challenges to transportation infrastructure. While machine learning has shown promise in hazard prediction, conventional qualitative methods are often subjective, and single machine learning models are prone to overfitting...

Ausführliche Beschreibung

Bibliografische Detailangaben

Hauptverfasser:	Xueyuan Li, Lu Zhang, Yuefeng Lu, Zongshun Tian, Yu Yan, Shuaibing Zhao, Peng Xie, Weijun Zhao
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	Taylor & Francis Group 2026-12-01
Schriftenreihe:	Geomatics, Natural Hazards & Risk
Schlagworte:	Road hazards collapse hazards machine learning coupled modelling susceptibility analysis
Online-Zugang:	https://www.tandfonline.com/doi/10.1080/19475705.2026.2617031
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