Full-Text Search:
Home|Journal Papers|About CNKI|User Service|FAQ|Contact Us|中文
《Dam Observation and Geotechnical Tests》 2002-04
Add to Favorite Get Latest Update

ARTIFICIAL NEURAL NETWORK-BASED DAILY STREAMFLOW FORECASTING

Zhang Jingjing, Jiang Tiebing, Kang Ling, Quan Xianzhang (Huazhong University of Science and Technology, Wuhan 430074, China)  
This paper presents the process of an artificial neural network (ANN) based daily streamflow forecasting model for the Three Gorges Yichang station. The ANN structure, including the selection of input variables, the number of input variables, the size of hidden layers, and the recursive ANN model, is discussed. The ANN-based model established can forecast daily streamflow profiles seven days ahead of time. The forecast result is satisfactory
【Fund】: 武汉市晨光计划资助项目 (2 0 0 0 5 0 0 40 2 8)
【CateGory Index】: P332
Download(CAJ format) Download(PDF format)
CAJViewer7.0 supports all the CNKI file formats; AdobeReader only supports the PDF format.
©2006 Tsinghua Tongfang Knowledge Network Technology Co., Ltd.(Beijing)(TTKN) All rights reserved