物理学报2012，Vol.61Issue(8)：90-96,7.
基于小波回声状态网络的混沌时间序列预测
Chaotic time series prediction based on wavelet echo state network
宋彤 1李菡1
作者信息
- 1. 大连理工大学电子信息与电气工程学部,大连116023
- 折叠
摘要
Abstract
Chaos is widespread in nature and human society, so the prediction of chaotic time series is very important. In this paper, we propose a new chaotic time series prediction model - echo state network based on wavelet, which can effectively overcome the ill-posed problem that exists in traditional echo state networks. And it also has a good generalization ability. Three time series are used to test the new model, i.e., Lorenz time series, Lorenz time series with added noise and batch reactor vessel temperature time series. Results suggest that the new proposed method can achieve a higher predictable accuracy, better generalization and more stable prediction results than traditional echo state networks.关键词
小波分解/回声状态网络/小波回声状态网络/混沌时间序列预测Key words
wavelet decomposition/echo state networks/echo state networks based on wavelet/chaotic time seriesprediction分类
数理科学引用本文复制引用
宋彤,李菡..基于小波回声状态网络的混沌时间序列预测[J].物理学报,2012,61(8):90-96,7.
