By Topic

Prediction of Railway Passenger Traffic Volume Based on Weighted LS-SVM

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
$33 $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

3 Author(s)
Hu Han ; Sch. of Math., Phys. & Software Eng., Lanzhou Jiaotong Univ., Lanzhou ; Jian-Wu Dang ; En-En Ren

In prediction of railway passenger traffic volume based on support vector regression, different input points make different contribution to the predictive function. A new prediction method for railway passenger volume, named weighted LS-SVM, is presented in this paper, different weighting factors are assigned to each input points by the linear interpolation function. The railway passenger volume from 1985 to 2002 are used and the results show that the weighted LS-SVM outperforms the standard LS-SVM.

Published in:

Intelligent Computation Technology and Automation (ICICTA), 2008 International Conference on  (Volume:1 )

Date of Conference:

20-22 Oct. 2008