• DocumentCode
    504476
  • Title

    Traveling time prediction using isolation rules

  • Author

    Shimada, Kaoru ; Hirasawa, Kotaro

  • Author_Institution
    Poduction & Syst. Res. Center, Waseda Univ., Fukuoka, Japan
  • fYear
    2009
  • fDate
    18-21 Aug. 2009
  • Firstpage
    153
  • Lastpage
    158
  • Abstract
    A method for traveling time prediction is proposed using genetic network programming (GNP) based data mining. The method extracts the rules named Isolation Rules, that is, a kind of association rules having the consequent part with the narrow distribution of continuous values. A set of isolation rules is applied to continuous value prediction. The database of the traveling time of the focused route with traffic information is generated and isolation rules on the traveling time of the route are extracted. Traveling time prediction is done considering the matching rate of the isolation rules with the current traffic conditions.
  • Keywords
    data mining; genetic algorithms; prediction theory; association rules; data mining; genetic network programming; isolation rules; traffic information; traveling time prediction; value prediction; Association rules; Data mining; Databases; Economic indicators; Genetics; Data Mining; Evolutionary Computation; Genetic Network Programming; Prediction; Traffic Analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    ICCAS-SICE, 2009
  • Conference_Location
    Fukuoka
  • Print_ISBN
    978-4-907764-34-0
  • Electronic_ISBN
    978-4-907764-33-3
  • Type

    conf

  • Filename
    5333405