水利信息化
水利信息化
수리신식화
WATER RESOURCES INFORMATIONZATION
2015年
2期
18-23
,共6页
EMD分解%EEMD分解%时间序列分析%绕坝渗流预测%耦合模型
EMD分解%EEMD分解%時間序列分析%繞壩滲流預測%耦閤模型
EMD분해%EEMD분해%시간서렬분석%요패삼류예측%우합모형
empirical mode decomposition%ensemble empirical mode decomposition%time series analysis%seepage around the dam forecasting%coupling model
为提高渗流量预报精度,以山西某水库古河床坝体绕渗流量为研究对象,首先基于MATLAB平台对其分别进行经验和集合经验模态分解,得到若干阶固有模态函数与1阶趋势分量,然后对各阶固有模态函数进行时序分析,建立求和自回归模型.最后通过拟合与预报精度2项指标对建立的EMD-ARI和EEMD-ARI模型进行比较分析.结果表明EEMD-ARI模型的预报精度明显高于EMD-ARI模型,可为大坝绕坝渗流耦合模型的构建及安全运行提供技术支持.
為提高滲流量預報精度,以山西某水庫古河床壩體繞滲流量為研究對象,首先基于MATLAB平檯對其分彆進行經驗和集閤經驗模態分解,得到若榦階固有模態函數與1階趨勢分量,然後對各階固有模態函數進行時序分析,建立求和自迴歸模型.最後通過擬閤與預報精度2項指標對建立的EMD-ARI和EEMD-ARI模型進行比較分析.結果錶明EEMD-ARI模型的預報精度明顯高于EMD-ARI模型,可為大壩繞壩滲流耦閤模型的構建及安全運行提供技術支持.
위제고삼류량예보정도,이산서모수고고하상패체요삼류량위연구대상,수선기우MATLAB평태대기분별진행경험화집합경험모태분해,득도약간계고유모태함수여1계추세분량,연후대각계고유모태함수진행시서분석,건립구화자회귀모형.최후통과의합여예보정도2항지표대건립적EMD-ARI화EEMD-ARI모형진행비교분석.결과표명EEMD-ARI모형적예보정도명현고우EMD-ARI모형,가위대패요패삼류우합모형적구건급안전운행제공기술지지.
In order to improve the prediction accuracy of seepage around, taking a reservoir ancient riverbed dam body seepage data in Shanxi Province as the research object, it is respectively decomposed by using the Empirical Mode Decomposition(EMD) and Ensemble Empirical Mode Decomposition(EEMD) method based on the MATLAB platform. It receives several Intrinsic Mode Functions(IMF) and one trend component, conducts time series analysis with all the IMF, builds Auto Regressive Integrated(ARI) model. It compares and analyzes the fitting results and prediction precision of two coupling models. The results show that the prediction accuracy of EEMD-ARI model is significantly higher than the EMD-ARI model, which can provide technical support for the construction of the dam seepage around dam coupling model and safe operation.
