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基于主成分分析和动态神经网络的时间序列预报
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.
作者姓名:严其艳
作者单位:东莞南博职业技术学院,广东,东莞,523083
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。

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
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.
Authors:YAN Qi-yan
Institution:YAN Qi-yan (Nanbo Institute of Technology, Dongguan,Guangdong,523083)
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.
Keywords:PCA
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