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.
Prediction of Railway Passenger Traffic Volume Based on Weighted LS-SVM
2008-10-01
336629 byte
Conference paper
Electronic Resource
English
Schienenverkehr - Prediction of passenger traffic 2020 - high speed railway traffic keeps successful
Online Contents | 2004
|Railway Passenger Flow Volume Prediction Model Analysis Based on Cobb-Douglas Function
Trans Tech Publications | 2012
|Railway Passenger Station Daily Traffic Working Plan Automation
British Library Conference Proceedings | 2007
|