基于EMD的降雨径流神经网络预测模型

Systems Engineering - Theory & Practice ›› 2009, Vol. 29 ›› Issue (1) : 152-158.

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PDF(650 KB)
Systems Engineering - Theory & Practice ›› 2009, Vol. 29 ›› Issue (1) : 152-158. DOI: 10.12011/1000-6788(2009)1-152
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Abstract

Through analyzing problem of wavelet analysis, the annual precipitation series from 1956 to 2000 in the sub-water resources region of upper Lanzhou is decomposed into muti-time scale series with EMD method. The results show that the precipitation series has periods that about 3, 4--8, 11 years, and the physical backgrounds and trends of the IMF sub-series are discussed. An
annual precipitation-runoff forecasting ANN model based on EMD is established, with the EMD decomposition series as input and the corresponding annual runoff as output. The study shows that, as a new and original signal decomposition method, Empirical Mode Decomposition namely EMD can be used as a tool to decompose hydrological time series into exact muti-time scale sub-series for finding their local change rule, and then to supply input variables with high quality and muti-level to enhance model
quality.

Key words

EMD / precipitation and runoff / ANN / forecasting model

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