Application of system NCF method to ice flood prediction of the Yellow River
Tóm tắt
Combined forecasts is a well-established procedure for improving forecasting accuracy which takes advantage of the availability of both multiple information and computing resources for data-intensive forecasting. Therefore, based on the combination of engineering fuzzy set theory and artificial neural network theory as well as genetic algorithms and combined forecast theory, the system Non-linear Combined Forecast (NCF) method is established for accuracy enhancement of prediction, especially of ice flood prediction. The NCF values from single forecast model for Inner Mongolia Reach of the Yellow River are given. The case shows that the method has clear physical meanings and precise consequences. Compared with any single model, the system NCF method is more rational, effective and accurate.
Tài liệu tham khảo
Bates JM, Granger CWJ (1969) The combination of forecasts. Operational Research Quarterly 20:451–468
Chen SY (1998a) Multiobjective decision making theory and application of neural network with fuzzy optimum selection. The Journal of Fuzzy Mathematics 6(4):957–967
Chen SY (1998b) Theory and application engineering fuzzy sets. Beijing: National defense industry press (in Chinese)
Chen SY, Nie XT (1999) Forecasting model of neural network with fuzzy pattern recognition and evolutionary simples method. The Journal of Fuzzy Mathematics 7(4):913–923
Chen SY, Guo Y, Wang, D G (2006) Intelligent forecasting mode and approach of mid and long term intelligent hydrological forecasting. Engineering Science 8(7):30–35
Chen SY, Ji HL (2005) Fuzzy optimization neural network approach for ice forecast in the Inner Mongolia Reach of the Yellow River. Hydrological Sciences Journal 50(2):319–330
HHOCMWR (Hydrologic & Hydraulic Operation Center of the Ministry of Water Resources) (1984) Ice regime of the Yellow River, Beijing: Chinese Hydraulic & Hydropower Press, 89–96
Ji HL (2002) Factor analysis for ice flood and model research for freeze-up time and break-up time in the inner mongolia reach of the Yellow River. Hohehot Inner Mongolia Agricultural University
Jan-Tai Kuo, Ying-Yi Wang, WU-Seng Lung (2006) A hybrid neural-genetic algorithm for reservoir water quality management. Water Research 40:1367–1376
Jin JL, Ding J (2002) Water resources systems engineering. Sichuan science and technology press, Chengdu
Nobuhiko Terui, Herman K. Van Dijk (2002) Combined forecasts from linear and nonlinear time series models. International Journal of Forecasting 18:421–438
Starosolszky O (1990) Effect of river barrages on ice regime. Journal of Hydrology 28(6):332–343
YRWCC, DHETU (The Yellow River Water Conservancy Committee & Department of Hydraulic Engineering, Tsinghua University) (1979) Ice flood in the downstream of the Yellow River, Beijing: Science Press,7–16
Zhang DJ (2002) Research on agent management, Forecast and Decision in Complex Water Environment and Resource System. Dalian: Dalian University of Technology
Zadeh LA (1965) Fuzzy Sets. Information Control 8:338–353