| 基于小波分解和支持向量机的ENSO预测试验 |
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| 引用本文： | 刘科峰,张军,陈奕德,李向军.基于小波分解和支持向量机的ENSO预测试验[J].解放军理工大学学报,2011,0(5):531-535. |
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| 作者姓名： | 刘科峰 张军 陈奕德 李向军 |
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| 作者单位： | 1．解放军理工大学 气象学院，江苏 南京 211101； 2.海军海洋水文气象中心，北京 100161 |
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| 摘 要： | 为了改善ENSO的预测效果,基于Nino综合区的海温距平时间序列,采用小波分解和最小二乘支持向量机结合的方法,引入多步递阶预测的思想,建立ENSO的预测模型.试验结果表明:基于小波分解和最小二乘支持向量机结合的多步预测方法,可以有效提高ENSO的预报精度.同时,该模型具有同时得到不同时效的预测结果,建模方便,计算效率高...
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| 关 键 词： | ENSO 小波分解 最小二乘支持向量机 多步递阶预测 |
| 收稿时间： | 2010-01-05 |
Compositive prediction of ENSO based on wavelet decomposition and support vector machine |
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| LIU Ke feng,ZHANG Jun,CHEN Yi de,LI Xiang jun.Compositive prediction of ENSO based on wavelet decomposition and support vector machine[J].Journal of PLA University of Science and Technology(Natural Science Edition),2011,0(5):531-535. |
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| Authors: | LIU Ke feng ZHANG Jun CHEN Yi de LI Xiang jun |
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| Institution: | 1．Institute of Meteorology, PLA Univ. of Sci. ＆ Tech., Nanjing 211101, China； 2．Navy Marine Hydrometeorological Center, Beijing 100161, China |
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| Abstract: | To improve the predictive effect of the EI Nino/La Nine and the Southern Oscillation(ENSO),based on the sea surface temperature anomaly time series of Nino integrated area, the method of the wavelet decomposition and the least squares support vector machine combined with multi step delivery forecast idea was introduced to establish ENSO prediction model. The analysis shows that the compositive multi step forecasting method based on the wavelet decomposition and the least squares support vector machine is efficient with much advantages in El Nino／La Nina events prediction, and that the forecasting results provide reference to the ENSO forecast. |
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| Keywords: | ENSO wavelet decomposition least squares support vector machines multi step delivery forecast |
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