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为提高年径流中长期预测的精度,提出了一种新的时间序列预测方法——基于EMD分解的AR模型,以汾河上游上静游、汾河水库、寨上和兰村四座水文站1956~2000年的年径流序列为例,首先利用经验模态分解(EMD)方法将四座水文站的年径流序列分解为若干个固有模态函数(IMF)分量和一个残余项分量,然后运用自回归(AR)模型分别对各阶IMF进行预测,最后将各阶预测值重构得到年径流量预测值与单独运用AR模型的预测结果进行比较。结果表明,运用基于EMD分解的AR模型对汾河上游年径流进行预测,其预测精度比单独运用AR模型的预测精度有明显提高,表明该方法可行、有效。
In order to improve the precision of mid-term and long-term prediction of annual runoff, a new time series prediction method is proposed based on the EMD model of ARD. Based on the hydrological stations of the upper reaches of the Fen River, the hydrological stations of Fenhe Reservoir, Zhaishang and Lancun, 1956 Taking the annual runoff series from 2000 to 2000 as an example, the annual runoff series of four hydrological stations are decomposed into several IMFs and one residual term component by empirical mode decomposition (EMD) (AR) model to predict each IMF respectively. Finally, the predicted values of annual runoff are reconstructed from the prediction of each order to be compared with the prediction results of AR model alone. The results show that forecasting the annual runoff in the upper reaches of Fen River using the AR model based on the EMD decomposition shows that the prediction accuracy is obviously higher than that of using the AR model alone, which shows that the method is feasible and effective.