Bus arrival time prediction using support vector machines

被引：197
|
作者：
Yu Bin [1 ]
Yang Zhongzhen [1 ]
Yao Baozhen [1 ]
机构：
[1] Dalian Maritime Univ, Transportat Coll, Dalian 116026, Peoples R China
来源：
JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS | 2006年 / 10卷 / 04期
关键词：
prediction; bus arrival time; support vector machine;
D O I：
10.1080/15472450600981009
中图分类号：
U [交通运输];
学科分类号：
08 ; 0823 ;
摘要：
Effective prediction of bus arrival time is central to many advanced traveler information systems. This article presents support vector machines (SVM), a new neural network algorithm, to predict bus arrival time. The objective of this paper is to examine the feasibility and applicability of SVM in vehicle travel time forecasting area. Segment, the travel time of current segment, and the latest travel time of next segment are taken as three input features. Bus arrival time predicted by the SVM is assessed with the data of transit route number 4 in Dalian economic and technological development zone in China and conclusions are drawn.
引用
收藏
页码：151 / 158
页数：8
相关论文
共 50 条
  • [1] Bus arrival time prediction using support vector machines
    Transportation College, Dalian Maritime University, Dalian 116026, China
    不详
    Xitong Gongcheng Lilum yu Shijian, 2007, 4 (160-164+176):
  • [2] BUS ARRIVAL TIME PREDICTION USING SUPPORT VECTOR MACHINE WITH GENETIC ALGORITHM
    Yang, M.
    Chen, C.
    Wang, L.
    Yan, X.
    Zhou, L.
    NEURAL NETWORK WORLD, 2016, 26 (03) : 205 - 217
  • [3] BUS TRAVEL TIME PREDICTION USING SUPPORT VECTOR MACHINES FOR HIGH VARIANCE CONDITIONS
    Bachu, Anil Kumar
    Reddy, Kranthi Kumar
    Vanajakshi, Lelitha
    TRANSPORT, 2021, 36 (03) : 221 - 234
  • [4] Using support vector machines for time series prediction
    Thiessen, U
    van Brakel, R
    de Weijer, AP
    Melssen, WJ
    Buydens, LMC
    CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2003, 69 (1-2) : 35 - 49
  • [5] Time Series Prediction Using Support Vector Machines: A Survey
    Sapankevych, Nicholas L.
    Sankar, Ravi
    IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE, 2009, 4 (02) : 24 - 38
  • [6] Prediction of the chaotic time series using support vector machines
    Cui, WZ
    Zhu, CC
    Bao, WX
    Liu, JH
    ACTA PHYSICA SINICA, 2004, 53 (10) : 3303 - 3310
  • [7] PREDICTION OF SEVERE ACCIDENT OCCURRENCE TIME USING SUPPORT VECTOR MACHINES
    Kim, Seung Geun
    No, Young Gyu
    Seong, Poong Hyun
    NUCLEAR ENGINEERING AND TECHNOLOGY, 2015, 47 (01) : 74 - 84
  • [8] Nonlinear prediction of chaotic time series using support vector machines
    Mukherjee, S
    Osuna, E
    Girosi, F
    NEURAL NETWORKS FOR SIGNAL PROCESSING VII, 1997, : 511 - 520
  • [9] Support Vector Regression for Bus Travel Time Prediction Using Wavelet Transform
    Yang Liu
    Yanjie Ji
    Keyu Chen
    Xinyi Qi
    JournalofHarbinInstituteofTechnology(NewSeries), 2019, 26 (03) : 26 - 34
  • [10] Using Support Vector Machines for numerical prediction
    Hussain, Shahid
    Khamisani, Vaqar
    INMIC 2007: PROCEEDINGS OF THE 11TH IEEE INTERNATIONAL MULTITOPIC CONFERENCE, 2007, : 88 - 92
12345