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

IMR OpenIR

	Combination kernel function least squares support vector machine for chaotic time series prediction
其他题名	Combination kernel function least squares support vector machine for chaotic time series prediction
	Tian ZhongDa 1; Gao XianWen 2; Shi Tong 3
	2014
发表期刊	ACTA PHYSICA SINICA
ISSN	1000-3290
卷号	63 期号:16
摘要	Considering the problem that least squares support vector machine prediction model with single kernel function cannot significantly improve the prediction accuracy of chaotic time series, a combination kernel function least squares support vector machine prediction model is proposed. The model uses a polynomial function and radial basis function to construct the kernel function of least squares support vector machine. An improved genetic algorithm with better convergence speed and precision is proposed for parameter optimization of prediction model. The simulation experimental results of Lorenz, Mackey-Glass, Sunspot-Runoff in the Yellow River and chaotic network traffic time series demonstrate the effectiveness and characteristics of the proposed model.
关键词	chaotic time series least squares support vector machine combination kernel function improved genetic algorithm
收录类别	CSCD
语种	英语
资助项目	[National Natural Science Foundation of China]
CSCD记录号	CSCD:5222172
引用统计	被引频次：14[CSCD] [CSCD记录]
文献类型	期刊论文
条目标识符	http://ir.imr.ac.cn/handle/321006/153551
专题	中国科学院金属研究所
作者单位	1.沈阳大学 2.东北大学 3.中国科学院金属研究所
推荐引用方式 GB/T 7714	Tian ZhongDa,Gao XianWen,Shi Tong. Combination kernel function least squares support vector machine for chaotic time series prediction[J]. ACTA PHYSICA SINICA,2014,63(16).
APA	Tian ZhongDa,Gao XianWen,&Shi Tong.(2014).Combination kernel function least squares support vector machine for chaotic time series prediction.ACTA PHYSICA SINICA,63(16).
MLA	Tian ZhongDa,et al."Combination kernel function least squares support vector machine for chaotic time series prediction".ACTA PHYSICA SINICA 63.16(2014).