The Study and Application of Two Combined Forecast Models Used in the Three Gorges Reservoir Long-Term Runoff Forecast

被引：0
|
作者：
Deng, Juan [1 ]
Zhou, Jianzhong [1 ]
Wang, Xue [1 ]
Guo, Jun [1 ]
机构：
[1] Huazhong Univ Sci & Technol, Sch Hydropower & Informat Engn, Wuhan 430074, Peoples R China
来源：
APPLIED INFORMATICS AND COMMUNICATION, PT 4 | 2011年 / 227卷
关键词：
Combined forecast model; runoff forecast; SVM; entropy weight;
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Long-term hydrological forecast is an integral part of hydrological forecast. Its level of accuracy plays an important role in the optimal allocation of water resources. In this paper, we bring out a combined forecast model based on Support Vector Machines (SVM) and entropy weight and apply it to the Three Gorges Reservoir runoff prediction. Compared to the Nearest Neighbor Bootstrapping Regressive model (NNBR), Mean Generating Function (MGF) and Automatic Regressive model (AR), the combined model is better than the individual model. It provides a reliable prediction method for long-term runoff forecast.
引用
收藏
页码：497 / 504
页数：8
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