| 基于结构可变的RBF神经网络的时间序列预测 |
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| 引用本文： | 张冬青,马宏伟,宁宣熙.基于结构可变的RBF神经网络的时间序列预测[J].中国管理科学,2010,18(3):83-89. |
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| 作者姓名： | 张冬青 马宏伟 宁宣熙 |
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| 作者单位： | 1. 南京农业大学工学院, 江苏南京210031;
2. 南京航空航天大学经济与管理学院, 江苏南京210016 |
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| 基金项目： | 国家自然科学基金资助项目(70571037);江苏省农机基金资助项目(gxz09003) |
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| 摘 要： | 基于神经网络的时间序列预测方法,需要正确确定网络结构,它关系到所建模型的合理性以及预测的准确性。目前确定网络结构的绝大多数方法,其网络结构一经训练确定便保持不变。然而现实中许多时间序列呈现非平稳性,其结构经常发生变化,这就要求网络结构能够动态可调,因此本文提出结构可变的径向基函数(RBF)神经网络预测模型。并采用序列蒙特卡罗(SMC)方法实现基于结构可变RBF网络的时间序列在线预测;最后采用CRU钢铁价格指数月数据进行实证研究,结果表明该模型的有效性。
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| 关 键 词： | 预测 时间序列 径向基函数神经网络 序列蒙特卡罗方法 |
| 收稿时间： | 2009-7-6 |
| 修稿时间： | 2010-5-30 |
Time Series Prediction Based on Variable Structure RBF Neural Networks |
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| ZHANG Dong-qing,MA Hong-wei,NING Xuan-xi.Time Series Prediction Based on Variable Structure RBF Neural Networks[J].Chinese Journal of Management Science,2010,18(3):83-89. |
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| Authors: | ZHANG Dong-qing MA Hong-wei NING Xuan-xi |
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| Institution: | 1. College of Engineering, Nanjing Agricultural University, Nanjing 210031, China;
2. College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China |
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| Abstract: | Suitable architecture is critical for a neural network to model time series and it determines forecast performance.So far,most methods assume that the architecture will keep fixed once it has been trained.However,many time series are nonlinear and their structures often change,which requires that the architecture of network should vary with time.Therefore,a variable structure radial basis function (RBF)neural network is proposed in this paper.Furthermore,sequential Monte Carlo(SMC)method is applied for time series on line prediction in the variable structure RBF network model.At last,the data of CRU global steel price index are analyzed,and experimental results indicate that the variable structure RBFnet work proposed is effective. |
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| Keywords: | prediction time series radial basis function neural networks sequential Monte Carlo method |
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