A LS-SVM Modeling Approach for Nonlinear Distributed Parameter Processes

被引：9
|
作者：
Qi, Chenkun [1 ]
Li, Han-Xiong [1 ]
机构：
[1] City Univ Hong Kong, Dept Mfg Eng & Eng Management, Hong Kong, Hong Kong, Peoples R China
来源：
2008 7TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-23 | 2008年
关键词：
distributed parameter system; spatio-temporal modeling; Karhunen-Loeve decomposition; least squares support vector machines;
D O I：
10.1109/WCICA.2008.4592985
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The distributed parameter system modeling from the input and output data is investigated. The spatio-temporal output of the system is measured at a finite number of spatial locations, while the input is assumed to be a finite-dimensional temporal variable. Firstly, Karhunen-Loeve (KL) decomposition is used for the time/space separation and the dimension reduction. Subsequently the spatio-temporal output is expanded in terms of a low dimensional Karhunen-Loeve spatial basis functions. Finally its temporal dynamic model is learned from the temporal coefficients by using least squares support vector machines (LS-SVM). The simulations are presented to show the effectiveness of this spatio-temporal modeling method.
引用
收藏
页码：569 / 574
页数：6
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