CLOCK ERROR PREDICTION USING LEAST SQUARES SUPPORT VECTOR MACHINES
1）National Time Service Centre, CAS, Xi’an 710600
Abstract To improve the prediction accuracy of satellite clock error, least squares support vector machines（LS-SVM） is employed. The impact of the kernel function type on LS-SVM is analyzed. Furthermore, the prediction accuracy is compared with that of the secondary are polynomial and grey system model. The results show that the LS-SVM method has higher accuracy than two other methods, and the linear kernel function is better than others for the method.
Key words ：
Least Squares Support Vector Machines（LS-SVM）
kernel function
satellite clock error
clock error prediction
grey system model
Received: 08 November 2012
Published: 18 April 2013
Cite this article:
Lei Yu,Zhao Danning. CLOCK ERROR PREDICTION USING LEAST SQUARES SUPPORT VECTOR MACHINES[J]. jgg, 2013, 33(2): 91-95.
Lei Yu,Zhao Danning. CLOCK ERROR PREDICTION USING LEAST SQUARES SUPPORT VECTOR MACHINES[J]. jgg, 2013, 33(2): 91-95.
URL:
http://www.jgg09.com/EN/ OR http://www.jgg09.com/EN/Y2013/V33/I2/91
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