多元混沌时间序列的因子回声状态网络预测模型

许美玲; 韩敏

doi:10.16383/j.aas.2015.c140604

多元混沌时间序列的因子回声状态网络预测模型

doi: 10.16383/j.aas.2015.c140604

许美玲,
韩敏^,

1.
大连理工大学电子信息与电气工程学部大连 116023

基金项目:

国家自然科学基金(61374154), 国家重点基础研究发展计划(973计划) (2013CB430403)资助

详细信息

作者简介:
许美玲大连理工大学电子信息与电气工程学部博士研究生. 主要研究方向为神经网络和多元时间序列预测.E-mail: xuml@mail.dlut.edu.cn

通讯作者:
韩敏大连理工大学电子信息与电气工程学部教授. 主要研究方向为神经网络, 模式识别和混沌时间序列预测. E-mail: minhan@dlut.edu.cn

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出版历程
- 收稿日期: 2014-08-19
- 修回日期: 2014-12-04
- 刊出日期: 2015-05-20

Factor Echo State Network for Multivariate Chaotic Time Series Prediction

XU Mei-Ling,
HAN Min^,

1.
Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116023

Funds:

Supported by National Natural Science Foundation of China (61374154), and National Basic Research Program of China (973 Program) (2013CB430403)

摘要

摘要: 针对采用回声状态网络预测多元混沌时间序列时存在的病态解问题, 本文建立了因子回声状态网络模型, 通过因子分析(Factor analysis, FA)方法提取高维储备池状态矩阵的公因子, 去除冗余和噪声成分. 利用降维后的因子变量与期望输出之间的线性回归关系, 求解网络未知参数. 基于Lorenz序列和大连月平均气温--降雨量的仿真实验验证了本文所提模型的有效性.
- 多元混沌时间序列 /
- 预测 /
- 回声状态网络 /
- 因子分析
Abstract: When an echo state network is used to predict multivariate time series, there may exist ill-posed problem. This paper proposes a novel prediction model, named factor echo state network, to solve the problem. It uses a factor analysis (FA) algorithm to extract the common factors of the reservoir matrix, and to remove the redundancies and noises. Then the unknown output weights are calculated by linear regression of the output and common factors. The model is used to predict Lorenz series and monthly average temperature-rainfall time series in Dalian, and simulation results substantiate its effectiveness.
- Multivariate chaotic time series /
- prediction /
- echo state network /
- factor analysis (FA)

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参考文献(24)

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多元混沌时间序列的因子回声状态网络预测模型

doi: 10.16383/j.aas.2015.c140604

作者简介:
许美玲大连理工大学电子信息与电气工程学部博士研究生. 主要研究方向为神经网络和多元时间序列预测.E-mail: xuml@mail.dlut.edu.cn

通讯作者:
韩敏大连理工大学电子信息与电气工程学部教授. 主要研究方向为神经网络, 模式识别和混沌时间序列预测. E-mail: minhan@dlut.edu.cn

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Factor Echo State Network for Multivariate Chaotic Time Series Prediction

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多元混沌时间序列的因子回声状态网络预测模型

doi: 10.16383/j.aas.2015.c140604

作者简介: 许美玲 大连理工大学电子信息与电气工程学部博士研究生. 主要研究方向为神经网络和多元时间序列预测.E-mail: xuml@mail.dlut.edu.cn

通讯作者: 韩敏 大连理工大学电子信息与电气工程学部教授. 主要研究方向为神经网络, 模式识别和混沌时间序列预测. E-mail: minhan@dlut.edu.cn

计量

出版历程

Factor Echo State Network for Multivariate Chaotic Time Series Prediction

计量

出版历程

目录

作者简介:
许美玲大连理工大学电子信息与电气工程学部博士研究生. 主要研究方向为神经网络和多元时间序列预测.E-mail: xuml@mail.dlut.edu.cn

通讯作者:
韩敏大连理工大学电子信息与电气工程学部教授. 主要研究方向为神经网络, 模式识别和混沌时间序列预测. E-mail: minhan@dlut.edu.cn