Study of Mid and Long-Term Runoff Forecast Based on Back-Propagation Neural Network

摘要：

Based on back-propagation (BP) neural network algorithm,by analyzing the data of Dan jiangkou reservoir many years historical runoff series in chronological order and introducing frequency factor,the neural network on mid and long-term runoff forecast has been established. And furthermore,the model has been applied to forecast and analyze the month runoff process of Dan jiangkou reservoir. The case study indicates that the forecasting accuracy of the model has been improved by introducing frequency factor. At the same time,the practical applicability of the model for mid and long-term runoff forecast is verified as well. So,this paper provides a new idea to mid and long-term runoff forecast of reservoirs.

关键词： BP neural network runoff forecast frequency analysis

作者: Kefei Li Changming Ji Yanke Zhang Wei Xie Xiaoxing Zhang

作者单位: The New and Renewable Energy of Beijing Key Laboratory,North China Electric Power University Beijing Jinsha River Hydropower,Yunnan Kunming,P. R. China

会议类型: 国际会议

会议名称: 2011 International Conference on Opto-Electronics Engineering and Information Science(2011光电电子工程与信息科学国际会议 ICOEIS 2011)

会议地点: 西安

会议语种:英文

页码: 1048-1051

在线出版日期: 2011-12-23（万方平台首次上网日期，不代表论文的发表时间）