Incomplete Phase Space Reconstruction Method Based on Subspace Adaptive Evolution Approximation
Joint Authors
Li, Tai-fu
Liu, Yu-cheng
Yao, Li-zhong
Jia, Wei
Zhou, Wei
Ge, Ji-ke
Source
Journal of Applied Mathematics
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-10-10
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
The chaotic time series can be expanded to the multidimensional space by phase space reconstruction, in order to reconstruct the dynamic characteristics of the original system.
It is difficult to obtain complete phase space for chaotic time series, as a result of the inconsistency of phase space reconstruction.
This paper presents an idea of subspace approximation.
The chaotic time series prediction based on the phase space reconstruction can be considered as the subspace approximation problem in different neighborhood at different time.
The common static neural network approximation is suitable for a trained neighborhood, but it cannot ensure its generalization performance in other untrained neighborhood.
The subspace approximation of neural network based on the nonlinear extended Kalman filtering (EKF) is a dynamic evolution approximation from one neighborhood to another.
Therefore, in view of incomplete phase space, due to the chaos phase space reconstruction, we put forward subspace adaptive evolution approximation method based on nonlinear Kalman filtering.
This method is verified by multiple sets of wind speed prediction experiments in Wulong city, and the results demonstrate that it possesses higher chaotic prediction accuracy.
American Psychological Association (APA)
Li, Tai-fu& Jia, Wei& Zhou, Wei& Ge, Ji-ke& Liu, Yu-cheng& Yao, Li-zhong. 2013. Incomplete Phase Space Reconstruction Method Based on Subspace Adaptive Evolution Approximation. Journal of Applied Mathematics،Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-513448
Modern Language Association (MLA)
Li, Tai-fu…[et al.]. Incomplete Phase Space Reconstruction Method Based on Subspace Adaptive Evolution Approximation. Journal of Applied Mathematics No. 2013 (2013), pp.1-9.
https://search.emarefa.net/detail/BIM-513448
American Medical Association (AMA)
Li, Tai-fu& Jia, Wei& Zhou, Wei& Ge, Ji-ke& Liu, Yu-cheng& Yao, Li-zhong. Incomplete Phase Space Reconstruction Method Based on Subspace Adaptive Evolution Approximation. Journal of Applied Mathematics. 2013. Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-513448
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-513448