• Mar 31, 2016 News!JACN Vol.3, No.3 has been indexed by EI (inspec)!   [Click]
  • Jun 24, 2016 News!JACN Vol.4, No.2 has been published with online version. 15 papres about advances in computer networks are published in this issue.   [Click]
  • Mar 31, 2016 News!JACN Vol.3, No.2 has been indexed by EI (inspec)!   [Click]
General Information
    • ISSN: 1793-8244
    • Frequency: Quarterly
    • DOI: 10.18178/JACN
    • Editor-in-Chief: Dr. Ka Wai Gary Wong
    • Executive Editor: Ms. Julia S. Ma
    • Abstracting/ Indexing: EI (INSPEC, IET), Engineering & Technology Digital Library, DOAJ, Electronic Journals Library, Ulrich's Periodicals Directory, International Computer Science Digital Library (ICSDL), ProQuest, and Google Scholar.
    • E-mail: jacn@ejournal.net
Editor-in-chief
Dr. Ka Wai Gary Wong
Department of Mathematics and Information Technology The Hong Kong Institute of Education, Hong Kong
It's a honor to serve as the editor-in-chief of JACN. I'll work together with the editors and reviewers to help the journal progress
JACN 2016 Vol.4(1): 70-74 ISSN: 1793-8244
DOI: 10.18178/JACN.2016.4.1.206

A GPS Time Series Prediction Model Based on CEEMD

Jia Lu, Xing Chen, and Shuo Feng
Abstract—A GPS time series prediction model is presented, based on Complete Ensemble Empirical Mode Decomposition (CEEMD), which has the advantage of improving the prediction accuracy greatly. CEEMD is a new and improved version of Empirical Mode Decomposition, which decomposes a non-linear and non-stationary time series into a finite and often small number of Intrinsic Mode Functions (IMFs) and a residual. For each IMF and the residual, appropriate models are recommended to model them respectively. Due to the reversibility of the decomposition, the final predicted result of the GPS time series is available by summing up predicted results of all IMFs and the residual. Experiment results show that the proposed model behaves much better than the classical time series prediction model.

Index Terms—GPS, time series, complete ensemble empirical mode decomposition, intrinsic mode functions.

Jia Lu is with China Defense Science and Technology Information Center, Beijing, China, he is also with Xichang Satellite Launch Center, Sichuan, China (e-mail: lujia661@126.com).
Xing Chen and Shuo Feng are with Xichang Satellite Launch Center, Sichuan, China (e-mail: chenxok@gmail.com, fsing1987@163.com).

[PDF]

Cite:Jia Lu, Xing Chen, and Shuo Feng, "A GPS Time Series Prediction Model Based on CEEMD," Journal of Advances in Computer Networks vol. 4, no. 1, pp. 70-74, 2016.

Copyright © 2008-2016. Journal of Advances in Computer Networks.  All rights reserved.
E-mail: jacn@ejournal.net