STUDY ON MIXED MODEL OF NEURAL NETWORK FOR FARMLAND FLOOD/DROUGHT PREDICTION*

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  • Abstract

    The paper concerns a flood/drought prediction model involving the continuation of time series of a predictand and the physical factors influencing the change of predictand.Attempt is made to construct the model by the neural network scheme for the nonlinear mapping relation based on multi-input and single output.The model is found of steadily higher predictive accuracy by testing the output from one and multiple stepwise predictions against observations and comparing the results to those from a traditional statistical model.
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Jin Long, Luo Ying, Guo Guang, Lin Zhenshan. 1997: STUDY ON MIXED MODEL OF NEURAL NETWORK FOR FARMLAND FLOOD/DROUGHT PREDICTION*. Journal of Meteorological Research, 11(3): 364-373.
Jin Long, Luo Ying, Guo Guang, Lin Zhenshan. 1997: STUDY ON MIXED MODEL OF NEURAL NETWORK FOR FARMLAND FLOOD/DROUGHT PREDICTION*. Journal of Meteorological Research, 11(3): 364-373.
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Jin Long, Luo Ying, Guo Guang, Lin Zhenshan. 1997: STUDY ON MIXED MODEL OF NEURAL NETWORK FOR FARMLAND FLOOD/DROUGHT PREDICTION*. Journal of Meteorological Research, 11(3): 364-373.
Jin Long, Luo Ying, Guo Guang, Lin Zhenshan. 1997: STUDY ON MIXED MODEL OF NEURAL NETWORK FOR FARMLAND FLOOD/DROUGHT PREDICTION*. Journal of Meteorological Research, 11(3): 364-373.
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