Close category search window
 

Online Time Series Forecasting Based on Biorthogonal Wavelet Kernel Support Vector Machine

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Huang Chao ; Sch. of Econ. & Manage., Southeast Univ., Nanjing, China ; Huang Li-Li ; Jiang Hong-Yan ; Zhong Wei-Jun

As a Special wavelet, biorthogonal wavelet has many advantages in signal processing. This paper constructs a new biorthogonal wavelet based on CDF method and constructs the biorthogonal wavelet kernel function. Then we study the update of incremental model and propose online forecasting algorithm. We research the algorithm based on biorthogonal wavelet kernel support vector machine (SVM) and use this algorithm to forecast the Chinese Csi 300 stock index futures at last. The experiment result shows the algorithm has ideal prediction effect.

Published in:
Computer Science & Service System (CSSS), 2012 International Conference on

Date of Conference: 11-13 Aug. 2012

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2013 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.