| 基于RBF-HMM模型的时间序列在线预测 |
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| 引用本文： | 张冬青,宁宣熙,刘雪妮.基于RBF-HMM模型的时间序列在线预测[J].系统工程学报,2010,25(1). |
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| 作者姓名： | 张冬青 宁宣熙 刘雪妮 |
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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，江苏省农机基金资助项目 |
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| 摘 要： | 针对非线性非高斯时间序列,提出观测噪声服从隐马尔可夫模型(HMM)的径向基函数(RBF)神经网络预测模型—RBF-HMM模型,该模型具有如下两个特点:(1)用隐节点数可变的RBF神经网络对时间序列进行非线性建模;(2)用HMM对非高斯噪声进行建模.并采用序列蒙特卡罗(SMC)方法实现RBF-HMM模型参数的动态调整和时间序列的在线预测.最后采用南京禄口国际机场日旅客吞吐量数据进行实证研究,结果表明该模型的有效性.
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| 关 键 词： | 预测 径向基函数神经网络 隐马尔可夫模型 序列蒙特卡罗方法 |
Time series on-line prediction based on RBF-HMM model |
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| ZHANG Dong-qing,NING Xuan-xi,LIU Xue-ni.Time series on-line prediction based on RBF-HMM model[J].Journal of Systems Engineering,2010,25(1). |
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| Authors: | ZHANG Dong-qing NING Xuan-xi LIU Xue-ni |
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| Institution: | ZHANG Dong-qing1,NING Xuan-xi2,LIU Xue-ni2(1.College of Engineering,Nanjing Agricultural University,Nanjing 210031,China,2.College of Economics & Management,Nanjing University of Aeronautics , Astronautics,Nanjing 210016,China) |
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| Abstract: | In order to cope with nonlinear and non-Gaussian time series,a RBF-HMM model,which is based on radial basis function(RBF) neural network with the assumption of measurement noise being a hidden Markov model(HMM) process,is proposed.The model has two characteristics as follows: 1) RBF neural networks with variable structure approximate nonlinear time series;2) Non-Gaussian noise is modeled by HMM.Furthermore,sequential Monte Carlo(SMC) method is used to adjust the parameters of RBF-HMM model dynamically and t... |
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| Keywords: | prediction radial basis function neural network hidden Markov model sequential Monte Carlo method |
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