| 基于主成分分析和动态神经网络的时间序列预报 |
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| 引用本文： | 严其艳. 基于主成分分析和动态神经网络的时间序列预报[J]. 中国西部科技, 2009, 8(10): 27-28 |
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| 作者姓名： | 严其艳 |
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| 作者单位： | 东莞南博职业技术学院,广东,东莞,523083 |
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| 摘 要： | 本文提出一种基于主成分分析（PCA）和动态神经网络的多变量时间序列预报方法，并对具体实例建立多变量时间序列模型。仿真实验结果表明该网络具有很强的学习能力和泛化能力，适合进行非线性时间序列预报。
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| 关 键 词： | PCA 动态递归神经网络 时间序列预报 |
Time Series Predicting Based on PCA and Dynamic Neural Network |
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| YAN Qi-yan. Time Series Predicting Based on PCA and Dynamic Neural Network[J]. Science and Technology of West China, 2009, 8(10): 27-28 |
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| Authors: | YAN Qi-yan |
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| Affiliation: | YAN Qi-yan (Nanbo Institute of Technology, Dongguan,Guangdong,523083) |
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| Abstract: | This paper proposes a multivariable time series predicting method based on principal component analysis （PCA） and dynamic neural network. And also a model is established as a concrete example. The simulating result shows that the network has strong study feature and generalization, and can be adapted to predict nonlinear time series. |
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| Keywords: | PCA |
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