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June 3, 2026WaterOpen Access

Intelligent Safety Monitoring of Reservoir Slopes: A Multi-Point Deformation Prediction Approach Considering Spatiotemporal Lag Effects

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Authors

JLJiachen LiangWCWenhan CaoTWTian Wang

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Overview

Randomized trial demonstrates advanced prediction of reservoir slope deformation, suggesting improved accuracy and stability.

Key Points

  • The study aims to improve prediction methods for reservoir slope deformation, accounting for spatiotemporal lag effects.
  • Developed a lag-aware clustering model (LAC-MOGP) using maximal information coefficient for factor screening.
  • Combined improved dynamic time warping with affinity propagation for clustering based on temporal correlations.
  • Embedded a DTW-based similarity weighting in a multi-output Gaussian Process for enhanced prediction.
  • LAC-MOGP achieved the lowest average root mean square error of 2.677 mm.
  • Average mean absolute error was minimized to 2.325 mm, indicating high prediction accuracy.
  • Outperformed traditional prediction methods in both accuracy and long-term stability.

Cite This Study

Liang et al. (2026) studied this question.

synapsesocial.com/papers/6a1fc696dee9eb8c0dce7a2chttps://doi.org/10.3390/w18111335
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