| 主成分分析法在我国税收预测中的应用 |
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| 引用本文： | 王文臣,汤秀芳.主成分分析法在我国税收预测中的应用[J].信阳师范学院学报(自然科学版),2006,19(4):504-506. |
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| 作者姓名： | 王文臣 汤秀芳 |
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| 作者单位： | 1. 信阳师范学院,河南,信阳,464000
2. 信阳职业技术学院,河南,信阳,464000 |
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| 摘 要： | 神经网络非常适用于复杂非线性系统的处理,已被广泛应用于经济预测中.针对经济预测中指标多、历史数据不足从而大大削弱神经网络的泛化能力问题,本文利用主成分分析法建立了税收的预测模型.结果显示:经主成分分析之后再进行预测,能从根本上降低神经网络规模,提高了神经网络的泛化能力.
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| 关 键 词： | 主成分分析法 神经网络 泛化能力 税收预测 |
| 文章编号： | 1003-0972（2006）04-0504-03 |
| 收稿时间： | 2006-03-16 |
| 修稿时间： | 2006年3月16日 |
Application in Tax Forecasting of Main Component Method |
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| WANG Wen-chen,TANG Xiu-fang.Application in Tax Forecasting of Main Component Method[J].Journal of Xinyang Teachers College(Natural Science Edition),2006,19(4):504-506. |
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| Authors: | WANG Wen-chen TANG Xiu-fang |
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| Institution: | 1. Xinyang Normal University, Xinyang 464000, China ;2. Xinyang Vocational and Technical Cortege, Xinyang 464000, China |
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| Abstract: | Artifical neural network is suitable for non-linear systems and is popularly applied in economic forecasting.But there are so many indexes and few historical numbers in ecoomic forecasting that weaken the generalization performance of the neural network.This article puts forward a tax forecasting model by use of main component method.Results indicate that reforecasting after the main component method can drop the scope of the neural network and improve its generalization performance. |
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| Keywords: | main component method the neural network gengeralization tax forecasting |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
