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

摘要：

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 LSSVM.

作者: Hu Han Jian-Wu Dang En-En Ren

作者单位: School of Mathematics, Physics and Software Engineering, Lanzhou Jiaotong University, Lanzhou 730070 School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China

会议类型: 国际会议

会议名称: International Conference on Intelligent Computation Technology and Automation(2008 智能计算技术与自动化国际会议 ICICTA 2008)

会议地点: 长沙

会议语种:英文

页码: 227-230

在线出版日期: 2008-10-20（万方平台首次上网日期，不代表论文的发表时间）