scholarly journals Local support vector machine prediction of spatiotemporal chaotic time series

2007 ◽  
Vol 56 (1) ◽  
pp. 67
Author(s):  
Zhang Jia-Shu ◽  
Dang Jian-Liang ◽  
Li Heng-Chao
Keyword(s):  
Time Series ◽  
Support Vector Machine ◽  
Chaotic Time Series ◽  
Support Vector ◽  
Local Support

Study on Prediction of Chaotic Time Series Using Least Squares Support Vector Machines

2014 ◽  
Vol 1061-1062 ◽  
pp. 935-938
Author(s):  
Xin You Wang ◽  
Guo Fei Gao ◽  
Zhan Qu ◽  
Hai Feng Pu
Keyword(s):  
Time Series ◽  
Support Vector Machine ◽  
Support Vector Machines ◽  
Least Squares ◽  
Prediction Accuracy ◽  
Chaotic Time Series ◽  
Support Vector ◽  
Vector Machines ◽  
Online Prediction ◽  
Better Than

The predictions of chaotic time series by applying the least squares support vector machine (LS-SVM), with comparison with the traditional-SVM and-SVM, were specified. The results show that, compared with the traditional SVM, the prediction accuracy of LS-SVM is better than the traditional SVM and more suitable for time series online prediction.

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