scholarly journals Combination kernel function least squares support vector machine for chaotic time series prediction

2014 ◽  
Vol 63 (16) ◽  
pp. 160508
Author(s):  
Tian Zhong-Da ◽  
Gao Xian-Wen ◽  
Shi Tong
Keyword(s):  
Time Series ◽  
Support Vector Machine ◽  
Least Squares ◽  
Kernel Function ◽  
Time Series Prediction ◽  
Chaotic Time Series ◽  
Support Vector ◽  
Chaotic Time Series Prediction

scholarly journals Chaotic time series prediction using filtering window based least squares support vector regression

2013 ◽  
Vol 62 (12) ◽  
pp. 120511
Author(s):  
Zhao Yong-Ping ◽  
Zhang Li-Yan ◽  
Li De-Cai ◽  
Wang Li-Feng ◽  
Jiang Hong-Zhang
Keyword(s):  
Time Series ◽  
Least Squares ◽  
Support Vector Regression ◽  
Time Series Prediction ◽  
Chaotic Time Series ◽  
Support Vector ◽  
Chaotic Time Series Prediction

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.

Sign in / Sign up

Export Citation Format

Share Document