DocumentCode :
3470743
Title :
Research on the Prediction of Urban Passenger Transport based on Support Vector Machine
Author :
Zhang, Wenfeng ; Shi, Zhongke ; Liu, Qin
Author_Institution :
Northwestern Polytech. Univ., Xi´´an
fYear :
2007
fDate :
18-21 Aug. 2007
Firstpage :
862
Lastpage :
865
Abstract :
The prediction model of urban passenger transport is proposed in this paper, which can provide the theoretical foundation for the government management to make decision and to predict passenger volume of urban transport accurately. The prediction model of urban passenger transport is established by using support vector machine (SVM), combining with the volume of the urban of passenger transport in Xi´an over years. The prediction model of urban passenger transport is validated, and the simulation results indicate that this prediction model is effective. Besides it has stronger fitting than the prediction based on BP neural network.
Keywords :
government data processing; prediction theory; support vector machines; traffic engineering computing; transportation; government management; support vector machine; urban passenger transport prediction; Automation; Cities and towns; Educational institutions; Logistics; Predictive models; Road transportation; Support vector machine classification; Support vector machines; Telecommunication traffic; Traffic control; Support vector machine; prediction model; urban passenger transport;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automation and Logistics, 2007 IEEE International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-1531-1
Type :
conf
DOI :
10.1109/ICAL.2007.4338685
Filename :
4338685
Link To Document :
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