| 引用本文: | 郅跃茹, 朱维彰, 诸 静.链式数据重组与神经网络在经济预测中的应用[J].控制理论与应用,2004,21(4):643~645.[点击复制] |
| ZHI Yue-ru, ZHU Wei-zhang, ZHU Jing.Application of the chain style data recombination methodand neural networks in macroeconomic forecast[J].Control Theory and Technology,2004,21(4):643~645.[点击复制] |
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| 链式数据重组与神经网络在经济预测中的应用 |
| Application of the chain style data recombination methodand neural networks in macroeconomic forecast |
| 摘要点击 1556 全文点击 1350 投稿时间：2002-03-25 修订日期：2003-09-02 |
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| DOI编号 |
| 2004,21(4):643-645 |
| 中文关键词 宏观经济预测 数据重组 神经网络训练 |
| 英文关键词 macroeconomic forecast data recombination neural networks training |
| 基金项目 |
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| 中文摘要 |
| 建立经济模型和基于模型对宏观经济进行预测,是经济运行质量评价、仿真、制定发展规划等所必不可少的.针对宏观经济预测的特殊性:样本少、时变性,提出了反向传播(BP)神经网络的链式数据重组训练方法,并用于实际经济预测.和原数据用于预测的结果相比,达到了较高的预测精度.同时,解决了BP神经网络难以确定隐结点数的问题. |
| 英文摘要 |
| It is necessary to model predict and model the economic system and for evalusating economic circulation,simulation,and making development programs.Based on the characteristics of the macroeconomic forecast,such as small data sets and time_varying,a chain_style data recombination method is presented,which is used for the back_propagation (BP) neural networks training.This method was applied to real macroeconomic forecast,and achieved the higher forecasting precision than the original data sets.It also solves the problem how to decide the hidden node numbers for the BP neural networks. |
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