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
Link To Document :
بازگشت