Landslide Deformation Uncertainty Quantification Using Conformalized Graph Neural Networks: A Case Study in Sichuan Province, China

Landslide Deformation Uncertainty Quantification Using Conformalized Graph Neural Networks: A Case Study in Sichuan Province, China

Landslide deformation prediction plays a crucial role in geohazard risk management, yet existing methods often struggle to quantify prediction uncertainties effectively. This paper presents GNN-CF, a novel framework that integrates Graph Neural Networks (GNN) with Conformal Prediction for reliable i...

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Bibliographic Details
Main Authors: Xiaopeng Ren, Wei Liu, Weiqi Yang, Lixuan Mao, Huajin Li
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Landslide deformation
graph neural networks
conformal prediction
interval forecasting
uncertainty quantification
Online Access:https://ieeexplore.ieee.org/document/10993416/
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