High accuracy behavior prediction of non-linear dynamic system with signal separation and support vector regression

Article type: Research Article

Authors: Wang, Jun

Affiliations: Department of Communication Engineering, Harbin University of Science and Technology, Harbin, Heilongjiang, China | E-mail: wangjunhit@chinaacc.com

Abstract: The behavior prediction of non-linear dynamic system is a challenging problem, especially when the system includes many independent subsystems. The observations from the complex dynamic system are the result of the interaction of multiple dynamic subsystems, which results in a loss of predictability. In this paper, signal separation technique is adopted to separate the observations of complex non-linear dynamic system in order to improve its predictability. And then local support vector regression technique is used to model the separated observations and make prediction. Finally, the prediction results are remixed as the original observation prediction or the behavior prediction of the complex non-linear dynamic system. The experimental results show that the proposed method improves the prediction accuracy substantially, which proves that signal separation can improve the predictability of complex non-linear dynamic system.

Keywords: Non-linear dynamic system, signal separation, support vector regression

DOI: 10.3233/JCM-170746

Journal: Journal of Computational Methods in Sciences and Engineering, vol. 17, no. 4, pp. 627-634, 2017