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

^*此作品的通讯作者

Dalian Maritime University
China University of Geosciences, Beijing

科研成果: 期刊稿件 › 文章 › 同行评审

6 引用（Scopus）

摘要

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.

源语言	英语
页（从-至）	158-160
页数	3
期刊	Dalian Haishi Daxue Xuebao/Journal of Dalian Maritime University
卷	34
期	4
出版状态	已出版 - 11月 2008
已对外发布	是

其它文件与链接

链接到 Scopus 的出版物

引用此

@article{08fbcf826cbb4705a905068740e4e3a7,

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",

journal = "Dalian Haishi Daxue Xuebao/Journal of Dalian Maritime University",

issn = "1006-7736",

publisher = "Editorial Office of Journal of Dalian Maritime University",

number = "4",

}

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

摘要

其它文件与链接

学术指纹

引用此