| 主成分分析与支持向量机相结合的区域降水预测应用 |
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| 引用本文： | 农吉夫.主成分分析与支持向量机相结合的区域降水预测应用[J].数学的实践与认识,2011,41(22). |
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| 作者姓名： | 农吉夫 |
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| 作者单位： | 广西民族大学 数学与计算机科学学院,广西 南宁 530006;广西混杂计算与集成电路设计分析重点实验室,广西 南宁 530006 |
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| 摘 要： | 将主成分分析和支持向量机回归相结合,以广西5、6月区域平均日降水量作为预报对象,进行区域日降水量预测研究.首先,整理分析大量的T213数值预报产品信息数据进行主成分分析,得到主成分数据序列;其次,根据主成分数据序列建立训练集训练支持向量机,并利用遗传算法优化参数;最后,输入支持向量机所需数据,得到主成分预测结果,建立广西日降水预报模型.实例计算结果表明,支持向量机回归模型比逐步回归模型有更好的预测能力.
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| 关 键 词： | 主成分分析 支持向量机 遗传算法 |
Regional Rainfall Forecast Based on Principal Component Analysis and Support Vector Machine |
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| NONG Ji-fu.Regional Rainfall Forecast Based on Principal Component Analysis and Support Vector Machine[J].Mathematics in Practice and Theory,2011,41(22). |
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| Authors: | NONG Ji-fu |
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| Institution: | NONG Ji-fu~(1,2) (1.College of Mathematics and Computer Science,Guangxi University for Nationalities,Nanning 530006,China) (2.Guangxi Key Laboratory of Hybrid Computation and IC Design Analysis,China) |
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| Abstract: | A scheme to forecast Regional Mean Rainfall is presented.This scheme combines the principal component analysis and the support vector regression,taking the regional average precipitation of Guangxi in May and June as the forecast object.First,a large number of information on the numerical forecasting products of T213 are turned into several time series data by the principal component analysis.Then,these principal component data are used to train the support vector machines,and a genetic algorithm is applied... |
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| Keywords: | principal component analysis support vector machine genetic algorithm |
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