Share:


Prediction of passenger flow on the highway based on the least square suppoert vector machine

    Yanrong Hu Affiliation
    ; Chong Wu Affiliation
    ; Hongjiu Liu Affiliation

Abstract

A support vector machine is a machine learning method based on the statistical learning theory and structural risk minimization. The support vector machine is a much better method than ever, because it may solve some actual problems in small samples, high dimension, nonlinear and local minima etc. The article utilizes the theory and method of support vector machine (SVM) regression and establishes the regressive model based on the least square support vector machine (LS-SVM). Through predicting passenger flow on Hangzhou highway in 2000–2008, the paper shows that the regressive model of LS-SVM has much higher accuracy and reliability of prediction, and therefore may effectively predict passenger flow on the highway.


First Published Online: 07 Jul 2011

Keyword : support vector machine, statistical learning theory, least square support vector machine, regressive model, passenger flow, prediction

How to Cite
Hu, Y., Wu, C., & Liu, H. (2011). Prediction of passenger flow on the highway based on the least square suppoert vector machine. Transport, 26(2), 197-203. https://doi.org/10.3846/16484142.2011.593121
Published in Issue
Jun 30, 2011
Abstract Views
555
PDF Downloads
472
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.