Application of system NCF method to ice flood prediction of the Yellow River |
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Authors: | Yu Guo |
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Institution: | (1) Department of Biological Sciences, University of Alberta, Edmonton, AB, T6G 2E9, Canada;(2) Wildlife Research Division, Science and Technology Branch, Environment Canada, 5320-122 Street, Edmonton, AB, T6H 3S5, Canada;(3) Manitoba Conservation, Box 28, 59 Elizabeth Drive, Thompson, MB, R8N 1X4, Canada |
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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. |
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Keywords: | |
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