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
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