江淮水利科技2026，Vol.21Issue(1)：11-15,5.DOI:10.20011/j.cnki.JHWR.202601002
基于互信息加权与时序嵌入的坝体裂缝预测模型
Dam crack prediction model based on mutual information weighting and temporal embedding
摘要
Abstract
To address the nonlinear associations and multi-scale temporal dependencies in multi-source heterogeneous data from dam crack monitoring,this paper proposed a hybrid prediction model(M-GEX)based on mutual information weighting and temporal embedding fusion.Firstly,the model quantified and weighted input features using mutual information,then exteacted multi-dimensional statistical features reflecting short-term dynamics through sliding windows,and generated low-dimensional temporal embeddings containing long-term dependencies using a GRU encoder.These features were concatenated and fed into an XGBoost regression model for prediction,with R2 and ERMS constituting the evaluation framework.In prediction tasks using three sets of monitoring data from Meishan Reservoir,the model achieved R2 values exceeding 0.87 and ERMS values below 1.84 across all datasets,demonstrating high accuracy in trend fitting and peak-valley prediction.M-GEX effectively integrates short-term statistical features with long-term times-series embeddings,enhancing both prediction accuracy and model interpretability.This approach provides an efficient and scalable technical solution for dam safety monitoring and early warning systems.关键词
大坝裂缝/互信息加权/时序嵌入/GRU编码器/结构健康监测Key words
dam cracks/mutual information weighting/temporal embedding/GRU encoder/structural health monitoring分类
建筑与水利引用本文复制引用
刘斌斌,王铭铭,朱小磊..基于互信息加权与时序嵌入的坝体裂缝预测模型[J].江淮水利科技,2026,21(1):11-15,5.基金项目
水利技术示范项目(SF-202414) （SF-202414）
安徽省水利厅科研及技术咨询项目(SLKJ202501-07) （SLKJ202501-07）
安徽省(水利部淮河水利委员会)水利科学研究院青年科技创新计划项目(KY202503) （水利部淮河水利委员会）
