Prediction of Inflow at Three Gorges Dam in Yangtze River with Wavelet Network Model

被引：79

作者：

Wang, Wensheng ^{[1
,3
]}

Jin, Juliang ^{[2
]}

Li, Yueqing ^{[3
]}

机构：

[1] Sichuan Univ, State Key Lab Hydraul & Mt River Engn, Chengdu 610065, Peoples R China

[2] Hefei Univ Technol, Coll Civil Engn, Hefei 230009, Peoples R China

[3] CMA, Chengdu Inst Plateau Meteorol, Chengdu 610072, Peoples R China

来源：

WATER RESOURCES MANAGEMENT | 2009年 / 23卷 / 13期

基金：

美国国家科学基金会;

关键词：

Wavelet analysis; Artificial neural network; Wavelet network model; Prediction of runoff; Three Gorges dam; NEURAL-NETWORK; RAINFALL;

D O I：

10.1007/s11269-009-9409-2

中图分类号：

TU [建筑科学];

学科分类号：

081407 [建筑环境与能源工程];

摘要：

A wavelet network model is developed to predict the inflow of Three Gorges dam in Yangtze River, China. The model makes use of the multi-resolution analysis of wavelet analysis and the nonlinear capability of artificial neural network. The short and long term input runoff of Three Gorges dam, such as annual mean discharge, seasonal mean discharge of 10 days period, daily mean discharge and annual maximum flood peak discharge, have been predicted with the wavelet network model (WNM). At the same time a kind of threshold auto-regressive model (TAR) has also applied for those predictions. The comparison of WNM with TAR has been executed. The results show that the accuracy of model predictions with WNM is generally better than that with TAR. The suggested wavelet network model is functional and feasible for runoff prediction.

引用

页码：2791 / 2803

页数：13

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