Global Navigation Satellite System-Based Deformation Monitoring of Hydraulic Structures Using a Gated Recurrent Unit–Attention Mechanism

Le résumé fourni par la source

Accurate monitoring of ground deformation is crucial for ensuring the safety and stability of hydraulic structures. Current deformation monitoring techniques often face challenges such as limited accuracy and robustness, particularly in complex environments. In this study, we propose a comprehensive method for Global Navigation Satellite System (GNSS) deformation monitoring in hydraulic structures by integrating the strengths of Gated Recurrent Units (GRUs) and Autoregressive Attention mechanisms. This approach enables efficient modeling of long-term dependencies while focusing on critical time steps, thereby enhancing prediction accuracy and robustness, especially in multi-step forecasting tasks. Experimental results show that the proposed GRU–Attention model achieves millimeter-level multi-step prediction accuracy, with predictions closely matching actual deformation data. Compared to the traditional method, the GRU–Attention model improves prediction accuracy by approximately 37%. The model’s attention mechanism effectively captures both short-term variations and long-term trends, ensuring accurate predictions even in complex scenarios. This research advances the field of GNSS deformation monitoring for hydraulic structures, providing valuable insights for engineering decision-making and risk management, ultimately contributing to enhanced infrastructure safety.

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