New sparse least squares support vector machine algorithm

2009 ◽  
Vol 29 (6) ◽  
pp. 1559-1562 ◽  
Author(s):  
Zong-liang WU ◽  
Heng DOU
Author(s):  
Hammam Tamimi ◽  
Dirk Söffker

This paper investigates modeling of flexible structures by means of the least squares support vector machine (LS-SVM) algorithm. Modeling is the first step to obtain a suitable model-based controller for any given system. Accurate modeling of a flexible structure based on experimental data using LS-SVM algorithm requires less knowledge about the physical system. Least squares support vector machine algorithm can achieve global and unique solution when compared with other soft computing algorithms. Also, LS-SVM algorithm requires less training time. In this paper, the successful use of support vector machine algorithm to model the flexible cantilever is demonstrated. The acquired model is able to provide accurate prediction of the system output under different operating conditions. Experimental results demonstrate the efficiency and high precision of the proposed approach.


2009 ◽  
Vol 19 (2) ◽  
pp. 194-198 ◽  
Author(s):  
Xiao-hu ZHAO ◽  
Gang WANG ◽  
Ke-ke ZHAO ◽  
De-jian TAN

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