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应用科学学报 ›› 2004, Vol. 22 ›› Issue (3): 411-414.

• 论文 • 上一篇    下一篇

基于小波分析的径向基神经网络年径流预测

蒋晓辉1, 刘昌明1,2   

  1. 1 北京师范大学环境科学研究所 北京 100875;
    2 国科学院地理科学与资源研究所 北京 100101
  • 收稿日期:2003-04-04 修回日期:2003-06-27 出版日期:2004-09-30 发布日期:2004-09-30
  • 作者简介:蒋晓辉(1972-),男,湖南永州人,博士生;刘昌明(1934-),男,湖南岳阳人,教授,博导,院士.
  • 基金资助:
    国家重点基础研究规划资助项目(G1999043601)

Radial Basis Function Networks Based on Wavelet Analysis for the Annual Flow Forecast

JIANG Xiao-hui1, LIU Chang-ming1,2   

  1. 1. Institute of Environmental Science, Beijing Normal University, Beijing 100875, China;
    2. Institute of Geographic Science and Natural Resources Research, CAS, Beijing 100101, China
  • Received:2003-04-04 Revised:2003-06-27 Online:2004-09-30 Published:2004-09-30

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81

被引次数

51

摘要： 对年径流的预测采用基于小波分析的径向基神经网络模型,从时频分析角度出发,把水文年径流序列分解成不同的频率成分,用径向基神经网络对小波分解的周期和趋势频率成分分别进行预测,然后通过小波重构得到水文时间序列,从而可以对未来的径流变化情况进行描述.

关键词: 黄河, 年径流预测, 小波分析, 径向基神经网络

Abstract: In this paper, radial basis function networks based on the wavelet analysis method is introduced to forecast hydrologic time series. Firstly the hydrologic time series is decomposed to different frequency components with wavelet analysis. Then the artificial neural network is used in multi-scale forecasting of these coefficients. Finally, based on the formula reconstructed, the forecasted hydrologic time series is obtained. The effectiveness of this method is verified by an example.

Key words: Yellow River, flow forecasting, radial basis function networks, wavelet analysis

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