%0 Journal Article
%T A novel GM(1, 2) forecasting model with parameters identified recursively<br>参数由递推辨识的新型GM(1,2)预测模型
%A LEI Ming-li
%A FENG Zu-ren
%A <br>雷鸣雳
%A 冯祖仁
%J 控制理论与应用
%D 2013
%I 
%X To improve the prediction performance, we propose a novel GM(1,2) model for prediction. The recursive prediction equations are derived directly from the definition of the model. The parameters of prediction equations are identified by using the particle swarm optimization algorithm (PSO). Typical numerical examples are given to demonstrate that the novel GM(1,2) model provides faster convergence rate and higher prediction precision than conventional GM(1,2) models and other improved GM(1,2) models mentioned in references.
%K grey prediction
%K GM(1
%K 2) model
%K parameter identification
%K particle swarm optimization (PSO)<br>灰色预测
%K GM(1
%K 2)模型
%K 参数辨识
%K 粒子群算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=9E8FDCFB8FA1D09F7282B9383E35D167&yid=FF7AA908D58E97FA&vid=340AC2BF8E7AB4FD&iid=0B39A22176CE99FB&sid=FD7C952458BFB5D8&eid=FE4C96E058BB2280&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=0&reference_num=0