| 多元混沌时间序列的因子回声状态网络预测模型 |
| |
| 引用本文： | 许美玲,韩敏.多元混沌时间序列的因子回声状态网络预测模型[J].自动化学报,2015,41(5):1042-1046. |
| |
| 作者姓名： | 许美玲 韩敏 |
| |
| 作者单位： | 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 |
| |
| 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.
|
| 关 键 词： | 多元混沌时间序列 预测 回声状态网络 因子分析 |
| 收稿时间： | 2014-08-19 |
Factor Echo State Network for Multivariate Chaotic Time Series Prediction |
| |
| XU Mei-Ling,HAN Min.Factor Echo State Network for Multivariate Chaotic Time Series Prediction[J].Acta Automatica Sinica,2015,41(5):1042-1046. |
| |
| Authors: | XU Mei-Ling HAN Min |
| |
| Affiliation: | 1.Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116023 |
| |
| 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. |
| |
| Keywords: | Multivariate chaotic time series prediction echo state network factor analysis (FA) |
|
| 点击此处可从《自动化学报》浏览原始摘要信息 |
|
点击此处可从《自动化学报》下载全文 |
|
