Characterizing Seasonality and Trend From In Situ Time‐Series Observations Using Explainable Deep Learning for Ground Deformation Forecasting

• Published in: Journal of geophysical research. Machine learning and computation Vol. 1; no. 2
• Main Authors: Ma, Zhengjing, Mei, Gang, Xu, Nengxiong
• Format: Journal Article
• Language: English
• Published: 01.06.2024
• Subjects: deep learning explainable neural network; geohazards; ground deformation forecasting; seasonality; time‐series observations; trend

Ground deformation, a critical indicator of geohazard evolution, exhibits both seasonal fluctuations and long‐term trend changes. This study explores interpretable deformation forecasting using an explainable deep learning approach, utilizing field observation data to extract and characterize these...