%0 Journal Article
%T Chaotic time series prediction based on wavelet echo state network<br>基于小波回声状态网络的混沌时间序列预测
%A Song Tong
%A Li Han
%A <br>宋彤
%A 李菡
%J 物理学报
%D 2012
%I 
%X 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.
%K wavelet decomposition
%K echo state networks
%K echo state networks based on wavelet
%K chaotic time series prediction<br>小波分解
%K 回声状态网络
%K 小波回声状态网络
%K 混沌时间序列预测
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=6E709DC38FA1D09A4B578DD0906875B5B44D4D294832BB8E&cid=47EA7CFDDEBB28E0&jid=29DF2CB55EF687E7EFA80DFD4B978260&aid=78F360FC29C47911F584084EC144EA7D&yid=99E9153A83D4CB11&vid=1D0FA33DA02ABACD&iid=5D311CA918CA9A03&sid=AFCF73D7403C63F1&eid=EE0A6A1C71639E1B&journal_id=1000-3290&journal_name=物理学报&referenced_num=0&reference_num=15