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November 14, 2025WaterOpen Access

Intelligent Prediction Based on NRBO–LightGBM Model of Reservoir Slope Deformation and Interpretability Analysis

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Authors

JCJiang ChenJSJiwan SunYXYang Xia

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Overview

Intelligent prediction method improves slope deformation modeling in reservoirs, indicating enhanced risk management.

Key Points

  • To develop a predictive framework for slope deformation using the NRBO-LightGBM model to improve interpretability and accuracy.
  • Developed a hybrid framework combining LightGBM with NRBO for hyperparameter tuning.
  • Utilized unsupervised clustering to identify temporal associations among monitoring points.
  • Applied SHAP analysis for interpreting the contributing factors affecting slope deformation.
  • Achieved a 22.8% reduction in RMSE and an 11.4% increase in R2 compared to conventional models.
  • Attained a 21.5% lower RMSE and a 15.5% higher R2 relative to baseline LightGBM model.
  • SHAP analysis revealed temporal accumulation and seasonal variations were primary factors influencing deformation.

Cite This Study

Chen et al. (2025) studied this question.

synapsesocial.com/papers/692519a2c0ce034ddc353c50https://doi.org/10.3390/w17223248
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