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
  • [31] Anomaly Detection in Time Series Data Using Support Vector Machines
    Yokkampon, Umaporn
    Chumkamon, Sakmongkon
    Mowshowitz, Abbe
    Hayashi, Eiji
    PROCEEDINGS OF THE 2021 INTERNATIONAL CONFERENCE ON ARTIFICIAL LIFE AND ROBOTICS (ICAROB 2021), 2021, : 581 - 587
  • [32] Prediction the Direction of SET50 Index Using Support Vector Machines
    Rungruang, Chongkolnee
    Srichaikul, Wilawan
    Chanaim, Somsak
    Sriboonchitta, Songsak
    THAI JOURNAL OF MATHEMATICS, 2019, 17 : 153 - 165
  • [33] Prediction-based portfolio selection model using support vector machines
    Hao, Cuiyan
    Wang, Jiaqian
    Xu, Wei
    Xiao, Yuan
    2013 SIXTH INTERNATIONAL CONFERENCE ON BUSINESS INTELLIGENCE AND FINANCIAL ENGINEERING (BIFE), 2014, : 567 - 571
  • [34] Prediction of Apnea of Prematurity in Neonates using Support Vector Machines and Random Forests
    Mago, Nikhit
    Srivastava, Shikhar
    Shirwaikar, Rudresh D.
    Acharya, Dinesh U.
    Lewis, Leslie Edward S.
    Shivakumar, M.
    PROCEEDINGS OF THE 2016 2ND INTERNATIONAL CONFERENCE ON CONTEMPORARY COMPUTING AND INFORMATICS (IC3I), 2016, : 693 - 697
  • [35] Exploiting uncertainty measures in compounds activity prediction using support vector machines
    Smusz, Sabina
    Czarnecki, Wojciech Marian
    Warszycki, Dawid
    Bojarski, Andrzej J.
    BIOORGANIC & MEDICINAL CHEMISTRY LETTERS, 2015, 25 (01) : 100 - 105
  • [36] Prediction of protein-protein interaction sites using support vector machines
    Koike, A
    Takagi, T
    PROTEIN ENGINEERING DESIGN & SELECTION, 2004, 17 (02): : 165 - 173
  • [37] Prediction of air pollutant levels using support vector machines: An effective tool
    Lu, W.
    Wang, W.
    Wang, X.
    Leung, A. Y. T.
    Proceedings of The Seventh International Conference on the Application of Artificial Intelligence to Civil and Structural Engineering, 2003, : 131 - 132
  • [38] Prediction of protein secondary structure using Bayesian method and support vector machines
    Nguyen, MN
    Rajapakse, JC
    ICONIP'02: PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON NEURAL INFORMATION PROCESSING: COMPUTATIONAL INTELLIGENCE FOR THE E-AGE, 2002, : 616 - 620
  • [39] Error correction of arrival time prediction in real time bus information system
    Kim, Seungil
    Lee, Chungwon
    Kim, Youngchan
    Lee, Seungjae
    Park, Dongjoo
    JOURNAL OF ADVANCED TRANSPORTATION, 2010, 44 (01) : 42 - 51
  • [40] Improved Prediction of Lysine Acetylation by Support Vector Machines
    Li, Songling
    Li, Hong
    Li, Mingfa
    Shyr, Yu
    Xie, Lu
    Li, Yixue
    PROTEIN AND PEPTIDE LETTERS, 2009, 16 (08): : 977 - 983
12345