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Jing Wang

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#graph neural networks Conference Oct 2026

TCN-GCN: a spatiotemporal neural network for multistep InSAR deformation prediction in geologically diverse regions

Accurate multi-step prediction of surface deformation monitored by Interferometric Synthetic Aperture Radar (InSAR) is critical for proactive disaster early warning in complex engineering environments. Existing approaches either neglect spatial dependencies among monitoring points or rely on recurrent architectures tha...

Yi-Yun Guo, Guang-He Li, Shu-Jing Dong et al. · 0 citations
Open access Jul 2026

Attention-based Spatio-Temporal Graph Convolutional Networks-enhanced deep reinforcement learning for adaptive traffic signal control in urban traffic networks.

A novel adaptive traffic signal control framework by integrating Attention-based Spatio-Temporal Graph Convolutional Networks (ASTGCN) with Multi-Agent Deep Deterministic Policy Gradient (MADDPG) is proposed, providing a scalable and data-driven solution for intelligent traffic signal control in urban traffic networks,...

Jing Wang, Xiaopeng Wang, Yang Mo et al. · 0 citations

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