| 非线性自回归时序模型研究及其预测应用 |
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| 引用本文： | 陈茹雯,黄仁.非线性自回归时序模型研究及其预测应用[J].系统工程理论与实践,2015,35(9):2370-2379. |
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| 作者姓名： | 陈茹雯 黄仁 |
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| 作者单位： | 1. 南京工程学院 汽车与轨道交通学院, 南京 211167;2. 东南大学 机械工程学院, 南京 211189 |
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| 基金项目： | 国家自然科学基金青年项目(51305194);江苏省自然科学基金(BK20130743,BK20130746);南京工程学院创新基金(CKJA201204) |
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| 摘 要： | 从函数逼近和系统辨识两个方面推导了非线性自回归时序模型(GNAR模型)的物理结构,通过公式推导及仿真数据研究GNAR模型与确定性实函数、经典时序模型和混沌序列的关系,明确GNAR模型对系统逼近的机理.以Lorenz系统输出的混沌序列和现代经典时序-太阳黑子序列为算例进行数据实验,证明了GNAR模型在建模和预测方面的优越性.
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| 关 键 词： | 非线性自回归时序模型 混沌序列 函数逼近 预测 |
| 收稿时间： | 2015-01-13 |
Research of general expression for nonlinear autoregressive model and its forecast application |
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| CHEN Ru-wen,HUANG Ren.Research of general expression for nonlinear autoregressive model and its forecast application[J].Systems Engineering —Theory & Practice,2015,35(9):2370-2379. |
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| Authors: | CHEN Ru-wen HUANG Ren |
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| Institution: | 1. School of Automobile and Rail Transit, Nanjing Institute of Technology, Nanjing 211167, China;2. School of Mechanical Engineering, Southeast University, Nanjing 211189, China |
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| Abstract: | The general expression for nonlinear autoregressive model (GNAR model) was derived based on the functional approximation or system identification. And the correlation was improved between GNAR model and real functions, classical time-series models or chaotic sequences through formula derivation and simulation data experiments to determine the approximation mechanism of GNAR model. Finally the fitting experiments of chaotic sequence obtained from Lorenz system and the modern time series data-sunspots show the superiority of GNAR model in modeling and forecasting. |
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| Keywords: | general expression for nonlinear autoregressive model chaos sequence functional approximation forecast |
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