| 基于支持向量机的短期GDP预测模型与应用研究 |
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| 引用本文： | 李运蒙,肖健华.基于支持向量机的短期GDP预测模型与应用研究[J].内蒙古大学学报(自然科学版),2004,35(4):438-441. |
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| 作者姓名： | 李运蒙 肖健华 |
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| 作者单位： | 五邑大学管理学院,广东,江门,529020 |
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| 基金项目： | 广东省自然科学基金项目(021349) |
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| 摘 要： | 支持向量机是最近几年国际上模式识别研究的热点,具有全局最优和良好的泛化能力.本文在理论分析江门市GDP预测指标体系的前提下,研究了基于SVM的预测方法,并运用实际数据进行建模和预测,获得了比较准确的预测结果.
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| 关 键 词： | 支持向量机 模式识别 预测 GDP |
| 文章编号： | 1000-1638(2004)04-0438-04 |
| 修稿时间： | 2004年1月5日 |
Application of Support Vector Machine Method in Short Term Prediction of GDP |
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| LI Yun-meng,XIAO Jian-hua.Application of Support Vector Machine Method in Short Term Prediction of GDP[J].Acta Scientiarum Naturalium Universitatis Neimongol,2004,35(4):438-441. |
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| Authors: | LI Yun-meng XIAO Jian-hua |
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| Abstract: | Support Vector Machine is one of the hot points in pattern recognition in research recent years in the world,since it has good performances such as global optimization and better generalization ability.Based on the theoretical analysis of the GDP prediction factors,a support vector machine prediction method is studied.The actual data are used to build the prediction model.It is shown that the predicition result is comparatively accurate. |
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| Keywords: | support vector machine pattern recognition prediction GDP |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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