| 摘要: |
| 根据1949-1988年登陆珠江口的热带气旋资料,运用了人工神经网络的一个典型模型──“反向传播”模型,建立了该地区35-49小时热带气旋登陆地点的预报模型,并应用于热带气旋登陆地点的预报,即珠江口的热带气旋登陆地点预报,其拟合最大相对误差不超过0.7%.结果表明,神经网络预报模型具有容错能力强、预报速度快的特点,可望成为热带气旋预报的有效辅助手段。 |
| 关键词: 热带气旋 人工神经网络 “反向传播”模型 |
| DOI： |
| 分类号: |
| 基金项目: |
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| ARTIFICIAL NEURAL NETWORK METHOD OF FORECASTING TROPICAL CYCLONE |
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Cai Yudong1, Lu Wencong2,3, Yao Linshen1
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1.Shanghai Metallurgical Institute, Academy of Sciences, Shanghai, 200050;2.Shanghai University the Chinese of Science &3.Technology
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| Abstract: |
| Based on the information of tropical cyclone landing at the Pearl River Gateway from the year 1949 to 1988, and with the help of a typical model of artificial neural network-B-P model,a 35－49 hour prediction model is established for the tropical cyclone landing point at the said region. And, after its application to the forecast of tropical cyclone landing point, namely, the forecast of tropical cyclone landing point at the Pearl River Gateway, the prediction model is found to have a maximum relative E-V tolerance of less than 0.7 %. The neural netowrk prediction model, as the result shows, features a stronger fault-tolerant ability as well as a faster prediction speed. Thus, it is expected to become an effective means to the forecast of tropical cyclone. |
| Key words: Tropical cyclone Artificial neural network Back-propagation model |
