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| 基于独立模型的非线性时间序列多步超前预测 | |
| 引用本文： | 杨臻明,岳继光,王晓保,萧蕴诗. 基于独立模型的非线性时间序列多步超前预测[J]. 上海交通大学学报, 2013, 47(10): 1626-1631 |
| 作者姓名： | 杨臻明 岳继光 王晓保 萧蕴诗 |
| 作者单位： | (1．同济大学 电子与信息工程学院, 上海, 201804; 2．上海申通轨道交通研究咨询有限公司, 上海, 201103) |
| 基金项目： | 国家自然科学基金(40872090)资助项目 |
| 摘 要： | 提出一种非线性时间序列的多步超前独立预测方法. 对比逐步递归方法和独立预测方法, 分析了积累误差对多步超前预测性能的影响. 采用递归神经网络(RNN)实现了独立预测方法, 建立了城市轨道交通能耗预测模型. 通过MATLAB训练和测试该模型, 比较了两种方法下的多步超前预测输出. 结果表明，独立预测方法的误差优于逐步递归方法. 最后指出了独立预测方法的优缺点及适用范围. |
| 关 键 词： | 非线性时间序列 多步超前独立预测 积累误差 递归神经网络 |
| 收稿时间： | 2012-12-14 |
Multistep-Ahead Independent Prediction of Nonlinear Time Series Based on Independent Model |
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| YANG Zhen ming,YUE Ji guang,WANG Xiao bao,XIAO Yun shi. Multistep-Ahead Independent Prediction of Nonlinear Time Series Based on Independent Model[J]. Journal of Shanghai Jiaotong University, 2013, 47(10): 1626-1631 | |
| Authors: | YANG Zhen ming YUE Ji guang WANG Xiao bao XIAO Yun shi |
| Affiliation: | (1. College of Electronic and Information Engineering, Tongji University, Shanghai 201804, China;2. Shanghai Shentong Rail Transit Research and Consultancy Co., Ltd., Shanghai 201103, China) |
| Abstract: | A multistep-ahead independent prediction approach of nonlinear time series was proposed. The step-by-step recurrent approach and the independent approach were compared, and the influence of accumulative error on the performance of multistep-ahead prediction was analyzed. The recurrent neural network (RNN) was used to realize the independent prediction approach, and the predictive model of urban rail transit is built, trained and tested by MATLAB. The predictive results showed that the error of independent prediction was smaller than that of step-by-step recurrent approach. The advantages and disadvantages of each approach were analyzed.Key words： |
| Keywords: | nonlinear time series multistep-ahead independent prediction accumulative error recurrent neural network |
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