%0 Journal Article
%T Support vector machine based direct inverse-model identification<br>基于支持向量机的直接逆模型辨识
%A ZHONG Wei-min
%A PI Dao-ying
%A SUN You-xian
%A <br>钟伟民
%A 皮道映
%A 孙优贤
%J 控制理论与应用
%D 2005
%I 
%X After a simple discussion of the principle of the inverse_model identification,a support vector machines(SVM) based direct inverse-model identification method is developed by using SVM's excellent ability of function approximation.According to the train data,linear and nonlinear systems' black-box identification is performed by using SVM with quadric polynomial and Gaussian RBF kernel respectively.Simulation results show that the performance of SVM based direct inverse-model is better than that of BP neural network in that it has better identification precision,quicker identification speed and stronger generalization ability.
%K inverse-model
%K support vector machine(SVM)
%K BP neural network
%K modeling and identification<br>逆模型
%K 支持向量机(SVM)
%K BP神经网络
%K 建模与辨识
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=B02F216E767D1971&yid=2DD7160C83D0ACED&vid=BC12EA701C895178&iid=0B39A22176CE99FB&sid=F416A9924F23B020&eid=85002451B65CE0D1&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=5&reference_num=7