水力发电2025，Vol.51Issue(3)：50-56,7.
水闸扬压力混合预测模型构建与解释
Construction and Interpretation of a Hybrid Prediction Model for Sluice Lift Pressure
摘要
Abstract
Aiming at the low interpretability of the existing"data-driven"models for sluice uplift pressure prediction results and the undeciphered contribution of factors to different components of the uplift pressure,an interpretable hybrid prediction model for sluice lift pressure based on the successive variational modal decomposition(SVMD)and ensemble learning algorithm is proposed.The model firstly adopts SVMD to decompose the uplift pressure into trend,seasonal and fluctuation terms,and then establishes corresponding models for different components based on the lightweight gradient boosting machine(LGBM)and summarizes the prediction results.In addition,the SHAP is used to analyze the influence and relationship of seepage influencing factors on the different components prediction results of the sluice uplift pressure.The engineering examples show that the proposed model improves the prediction performance by 87.1%on average compared with the single-algorithm model,and by 84.6%on average compared with the hybrid prediction model,which verifies the effectiveness of the model.At the same time,the interpretability of the model is improved.关键词
水闸扬压力预测/逐次变分模态分解/集成学习/SHAP/模型解释Key words
sluice lift pressure prediction/successive variational mode decomposition/ensemble learning/SHAP/model interpretation分类
水利科学引用本文复制引用
胡璟,王豹,王璐,龙俊,贝欣,孙远,曹文翰..水闸扬压力混合预测模型构建与解释[J].水力发电,2025,51(3):50-56,7.基金项目
国家自然科学基金资助项目(52379122) （52379122）
中央高校基础业务费(2019B69814) （2019B69814）
