应用科学学报 ›› 2007, Vol. 25 ›› Issue (1): 96-99.

• 论文 • 上一篇    下一篇

年径流预测的小波系数加权和模型

李亚娇, 沈冰, 李家科   

  1. 西安理工大学水利水电学院, 陕西西安 710048
  • 收稿日期:2005-12-28 修回日期:2006-04-11 出版日期:2007-01-31 发布日期:2007-01-31
  • 作者简介:李亚娇,博士生,研究方向:旱区水文水资源,E-mail:liyajiao@163.com;沈冰,教授,博导,研究方向:旱区水文水资源,E-mail:shenbing@xaut.edu.cn
  • 基金资助:

    国家科技攻关“西部开发”重大项目(2004BA901A13)

Weighted Summation of Wavelet Coefficients Model for Annual Runoff Prediction

LI Ya-jiao, SHEN Bing, LI Jia-ke   

  1. Institute of Water Resources and Hydro-electric Engineering, Xi'an University of Technology, Xi'an 710048, China
  • Received:2005-12-28 Revised:2006-04-11 Online:2007-01-31 Published:2007-01-31

摘要:

利用连续小波变换和小波方差分析年径流的周期特征,已被众多学者认可并应用于年径流的分析中。但这种方法只是一种定性预测,并不能作出比较明确的定量预测.本文在原有定性分析方法的基础上,提出基于年径流时间序列主周期小波系数加权求和预测周期成分的年径流预测模型.该方法更为有效地利用了小波分析的多分辨率特征,并可减小趋势成分的预测误差.经对千河流域年径流建模并检验,结果表明,文中所提出的预测方法可得到较为理想的预测结果,并可用于年径流时间序列预测.

关键词: 年径流预测, 小波系数, 加权求和, 时间序列

Abstract:

The method that analyzes the period characteristics of annual runoff with continuous wavelet transformation and wavelet variance has been widely used.However it only gives qualitative prediction results, but not quantitative results. Based on the primary qualitative method, we propose an annual runoff prediction model using weighted sum of wavelet coefficients of major periods to predict the periodic components.The method effectively takes advantage of the multiresolution characteristic of wavelet analysis, and can reduce prediction errors caused by trend components.The annual runoff data of Qianhe basin are used to build and check the model.The proposed method can provide better results useful in predicting annual runoff time series.

Key words: wavelet coefficients, weighted summation, annual runoff prediction, time series

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