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Time Dependency of Monthly Hydrologic Data Series of the Main Channel of Weihe River
Pages: 25-27
Year: Issue:  11
Journal: Yellow River

Keyword:  monthly runoff forecasttime dependencyneural networkWeihe River;
Abstract: Presently,most methods of runoff forecast require data sequence to have nature of time dependency,therefore,before carrying on the forecasting of time series,the first step should distinguish the time dependency. Taking Linjiacun Hydrologic Station and Xianyang Station of Weihe River as the object,using linear auto-regression model,it analyzed the degree of correlation of neighboring two monthly runoff series,studied their time dependency and using BP neural network model to carry on the monthly runoff forecast. The result shows that when degree of correlation of two neighboring monthly runoff ≥0. 7,dependency of data sequence is good,can be used for forecasting;when the pass rate of forecasting≥80%, monthly runoff series can be used for forecasting by using neural network model.
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