| 用神经网络法试报黄河三角洲汛期暴雨 |
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| 引用本文： | 郝家学,张经珍,等.用神经网络法试报黄河三角洲汛期暴雨[J].气象与环境科学,2000(3):19-21. |
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| 作者姓名： | 郝家学 张经珍 |
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| 作者单位： | 东营市气象局!山东东营257091 |
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| 摘 要： | 在天气学分型的基础上，用神经网络Back-Propagation(简称B－P）算法，以1990－1995年汛期（6月下旬－9月上旬）日本数值预报产品和实时资料若干气象要素作为预报因子，对黄河三角洲的汛期暴雨进行了试预报，预报准确率平均达70％，比主观预报准确率提高了50％以上。
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| 关 键 词： | 神经网络 黄河三角洲 暴雨 G－P算法 汛期 预报 |
Rainstorm Forecast of the Yellow River Delta Using the Neural Network Method |
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| HAO Jia-xue,ZHANG Jing-zhen,SUN Xiu-zhong,LIU Dun-xun,ZHANG Hong-wei.Rainstorm Forecast of the Yellow River Delta Using the Neural Network Method[J].Meteorological and Environmental Sciences,2000(3):19-21. |
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| Authors: | HAO Jia-xue ZHANG Jing-zhen SUN Xiu-zhong LIU Dun-xun ZHANG Hong-wei |
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| Abstract: | Based on the classification of synoptically meteorology,using the Back-Propagation algorithm of neural network,and by combining the numerical forecast products in Japan and the actual data from 1990 to 1995,so the rainstorm forecast of the Yellow River Delta is finally achieved,the average accuracy of forecasting can reach to 70%,which is enhanced 50% than subjective accuracy of forecasting . |
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| Keywords: | Neural network The Yellow River Delta Rainstorm Back-Propagation algorithm |
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