%0 Journal Article
%T An Application Study on Prediction and Analysis for Ideal Time Series Based on the SVM Method<br>支持向量机方法应用于理想时间序列的预测研究
%A MAO Yu-Qing
%A WANG Yong-Qing
%A WANG Ge-Li
%A <br>毛宇清
%A 王咏青
%A 王革丽
%J 气候与环境研究
%D 2007
%I 
%X The support vector machine (SVM) regression principle and basic ideas based on the statistical learning theory are introduced.This method is used to build forecasting models on the ideal time series from 33-mode Lorenz system,and especially the prediction on nonstationary time series are tested and analyzed.It is shown that the SVM method is available for both stationary series and nonstationary ones,and the results are developmental to prediction of real data.
%K support vector machine
%K nonstationary time series
%K forecast model<br>支持向量机
%K 非平稳时间序列
%K 预测建模
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=E62459D214FD64A3C8082E4ED1ABABED5711027BBBDDD35B&cid=28A2F569B2458C17&jid=484C10BAB5333C14751916EACFF8295F&aid=500D404BA6E5B7104D222381E7C9CDCA&yid=A732AF04DDA03BB3&vid=59906B3B2830C2C5&iid=94C357A881DFC066&sid=5AE7FA263C8A6D65&eid=6D25DD85174CF6DB&journal_id=1006-9585&journal_name=气候与环境研究&referenced_num=0&reference_num=14