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Application of system NCF method to ice flood prediction of the Yellow River

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  • Yu Guo

    (Ministry of Water Resources)

Abstract

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.

Suggested Citation

  • Yu Guo, 2009. "Application of system NCF method to ice flood prediction of the Yellow River," Fuzzy Information and Engineering, Springer, vol. 1(2), pages 191-204, June.
    • Handle: RePEc:spr:fuzinf:v:1:y:2009:i:2:d:10.1007_s12543-009-0015-z
    DOI: 10.1007/s12543-009-0015-z
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    References listed on IDEAS

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    1. Terui, Nobuhiko & van Dijk, Herman K., 2002. "Combined forecasts from linear and nonlinear time series models," International Journal of Forecasting, Elsevier, vol. 18(3), pages 421-438.
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