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

被引：1

作者：

Ilan, Ilu ^{[1
,2
]}

Dang, Jian-Wu ^{[2
]}

Ren, En-En ^{[2
]}

机构：

[1] Lanzhou Jiaotong Univ, Sch Math Phys & Software Engn, Lanzhou 730070, Peoples R China

[2] Lanzhou Jiaotong Univ, Sch Elect & Informat Engn, Lanzhou 730070, Peoples R China

来源：

INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTATION TECHNOLOGY AND AUTOMATION, VOL 1, PROCEEDINGS | 2008年

关键词：

D O I：

10.1109/ICICTA.2008.17

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

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 LS-SVM.

引用

页码：227 / +

页数：2

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