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利用神经网络计算方法建立太平洋副高活动的预报模型
ESTABLISHMENT OF PREDICTION MODEL FOR THE PACIFIC SUBTROPICAL HIGH USING NEURAL NETWORK CALCULATION METHOD
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摘要: 基于赤道附近海温和副热带高压相关性的观测和研究事实, 利用人工神经网络的BP模型及其优化算法建立了近赤道海温同西太平洋副热带高压面积指数之间的预报模型.该模型可根据月平均的近赤道海温和副高面积指数的前期分布, 预报出其后3个月副高面积指数的基本走向和变化趋势.该模型具有较高的拟合精度, 其预报效果和预报时效具有一定的实用意义.Abstract: Based on the observational facts and correlative study results about the equatorial SST and Subtropical High, a prediction model between West-Pacific Subtropical High and equatorial SST is established by using the BP neural network model and its improved calculation method. By using this model, we can predict Subtropical High's basic changes and trend ahead of 3 months according to the early data of equatorial SST and subtropical high. This prediction model has better coupling precision. The forecasting accuracy and valid time of this model are meaningful in application.
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Key words:
- Neural network;
- Prediction model;
- Pacific SST;
- Subtropical high
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