Application of support vector machines in bus travel time prediction

Bin Yu; Yong Lei Jiang; Bo Yu; Zhong Zhen Yang

Application of support vector machines in bus travel time prediction

Bin Yu^*
, Yong Lei Jiang
, Bo Yu^*
, Zhong Zhen Yang

^*Corresponding author for this work

Dalian Maritime University
China University of Geosciences, Beijing

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

To obtain the real-time road traffic condition and dispatch and dispatch the vehicle, as well as plan the conveyance, a method based on support vector machines (SVM) was developed to predict bus travel time. Tests on No.23 bus in Dalian show that the prediction accuracy of SVM model is higher than that of history mean prediction (HMP) model and artificial neural network (ANN) model.

Original language	English
Pages (from-to)	158-160
Number of pages	3
Journal	Dalian Haishi Daxue Xuebao/Journal of Dalian Maritime University
Volume	34
Issue number	4
State	Published - Nov 2008
Externally published	Yes

Keywords

Prediction
Public traffic vehicles
Support vector machine (SVM)
Travel-time

Cite this

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title = "Application of support vector machines in bus travel time prediction",

abstract = "To obtain the real-time road traffic condition and dispatch and dispatch the vehicle, as well as plan the conveyance, a method based on support vector machines (SVM) was developed to predict bus travel time. Tests on No.23 bus in Dalian show that the prediction accuracy of SVM model is higher than that of history mean prediction (HMP) model and artificial neural network (ANN) model.",

keywords = "Prediction, Public traffic vehicles, Support vector machine (SVM), Travel-time",

author = "Bin Yu and Jiang, \{Yong Lei\} and Bo Yu and Yang, \{Zhong Zhen\}",

year = "2008",

month = nov,

language = "英语",

volume = "34",

pages = "158--160",

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issn = "1006-7736",

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TY - JOUR

T1 - Application of support vector machines in bus travel time prediction

AU - Yu, Bin

AU - Jiang, Yong Lei

AU - Yu, Bo

AU - Yang, Zhong Zhen

PY - 2008/11

Y1 - 2008/11

N2 - To obtain the real-time road traffic condition and dispatch and dispatch the vehicle, as well as plan the conveyance, a method based on support vector machines (SVM) was developed to predict bus travel time. Tests on No.23 bus in Dalian show that the prediction accuracy of SVM model is higher than that of history mean prediction (HMP) model and artificial neural network (ANN) model.

AB - To obtain the real-time road traffic condition and dispatch and dispatch the vehicle, as well as plan the conveyance, a method based on support vector machines (SVM) was developed to predict bus travel time. Tests on No.23 bus in Dalian show that the prediction accuracy of SVM model is higher than that of history mean prediction (HMP) model and artificial neural network (ANN) model.

KW - Prediction

KW - Public traffic vehicles

KW - Support vector machine (SVM)

KW - Travel-time

UR - https://www.scopus.com/pages/publications/57749106708

M3 - 文章

AN - SCOPUS:57749106708

SN - 1006-7736

VL - 34

SP - 158

EP - 160

JO - Dalian Haishi Daxue Xuebao/Journal of Dalian Maritime University

JF - Dalian Haishi Daxue Xuebao/Journal of Dalian Maritime University

IS - 4

ER -

Application of support vector machines in bus travel time prediction

Abstract

Keywords

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