三峡大学学报（自然科学版）2024，Vol.46Issue(1)：1-6,6.DOI:10.13393/j.cnki.issn.1672-948X.2024.01.001
基于CEEMDAN和相关性分析的大坝位移预测
Dam Displacement Prediction Based on CEEMDAN and Correlation Analysis
摘要
Abstract
The dam displacement data is influenced by various factors and has non-stationary nonlinear characteristics.To address the problem of low data prediction accuracy,a CEEMDAN-PCCs-TCN-XGBoost combined prediction model is proposed.Taking the monitoring data of a certain gravity dam as an example,firstly,the CEEMDAN algorithm is introduced to capture the trend and fluctuation information of non-stationary data,and the PCCs algorithm is combined to determine the main factors affecting data fluctuations.Secondly,in order to improve prediction accuracy,the traditional HST model is used for trend information prediction,and the main factors are used as input variables for fluctuation information prediction.Finally,the TCN model and XGBoost model are respectively applied to predict the data,and the prediction result is accumulated.The prediction results are compared with models such as EEMD-ARIMA and EEMD-LSTM-MLR.The results show that the CEEMDAN-PCCs-TCN-XGBoost combined prediction model is more accurate in predicting dam displacement data with frequent fluctuations.关键词
混凝土大坝/变形预测/CEEMDAN/Pearson相关系数/时间卷积网络Key words
concrete dam/displacement prediction/CEEMDAN/Pearson correlation coefficient/time convolution network分类
建筑与水利引用本文复制引用
傅露莹,齐慧君,李同春,姜鹏辉,杜效鹄..基于CEEMDAN和相关性分析的大坝位移预测[J].三峡大学学报（自然科学版）,2024,46(1):1-6,6.基金项目
国家重点研发计划(2022YFC3005403) （2022YFC3005403）
中国电建集团科技项目(DJ-ZDXM-2021-10) （DJ-ZDXM-2021-10）
