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Prediction of Urban Surface Deformation by Integrating Time-Series InSAR and Spatiotemporal Dual-Driven Deep Learning

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NIAID Data Ecosystem2026-05-10 收录
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https://data.mendeley.com/datasets/6szg7mcbw2
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资源简介:
The document contains the core code for a spatio-temporal dual-driver prediction model, along with five benchmark models for comparison and validation: ARIMA, GRU, LSTM, XGboost, and Random Forest.
创建时间:
2026-03-18
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