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Sixth International Conference on Intelligent Systems Design and Applications (ISDA'06) Volume 1
Mid- and long term hydrologic forecasting for drainage area based on WNN and FRM
Jinan, China
October 16-October 18
ISBN: 0-7695-2528-8
Huicheng Zhou, Dalian University of Technology, China
Li Wu, Dalian University of Technology, China
Yu Guo, Dalian University of Technology, China
Mid- and long term hydrologic forecasting of drainage area is a difficult issue in engineering design and hydrological process simulation. Combined with wavelet neural network (WNN) to calculate and forecast the weight of model, fuzzy recognition model (FRM) is used to fit and predict mid- and long term hydrological phenomena, and the regression equation with correlation coefficient that more than 0.90 is adopted as fit equation to evaluate and verify this process. The result shows that this method is reasonable and simple, and it can be applied for forecasting work.
Index Terms:
Mid- and long term hydrologic forecasting; FRM; WNN; forecast factors
Citation:
Huicheng Zhou, Li Wu, Yu Guo, "Mid- and long term hydrologic forecasting for drainage area based on WNN and FRM," isda, vol. 1, pp.7-12, Sixth International Conference on Intelligent Systems Design and Applications (ISDA'06) Volume 1, 2006
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