DocumentCode
131659
Title
Research on Traffic Flow Algorithm
Author
Xiaoying Li
Author_Institution
Col. of Electr. & Informational Eng, Changsha Univ. of Sci. & Technol., Changsha, China
fYear
2014
fDate
10-11 Jan. 2014
Firstpage
556
Lastpage
560
Abstract
With the development of highway toll system is more and more perfect, the intelligent toll system attracts more and more attentions and gets very wide application. With the development of computer, communication and network technology communication technology, the toll system also has intelligent and network management. Tool system collects unremittingly a lot of toll flow date and other traffic information. We can predict traffic flow using the date of toll system base on neural network. At the paper, using the BP network and RBF network algorithm respectively, obtaining error ratio of each kind of vehicle type and total error ratio. Comparing result show which algorithm has low error rate.
Keywords
backpropagation; intelligent transportation systems; radial basis function networks; road pricing (tolls); road traffic; BP network; RBF network algorithm; intelligent toll system; neural network; traffic flow algorithm; traffic flow prediction; Error analysis; MATLAB; Mathematical model; Radial basis function networks; Training; Vehicles; BP Network; Error Ratio; RBF Network; Toll System; Traffic Flow;
fLanguage
English
Publisher
ieee
Conference_Titel
Measuring Technology and Mechatronics Automation (ICMTMA), 2014 Sixth International Conference on
Conference_Location
Zhangjiajie
Print_ISBN
978-1-4799-3434-8
Type
conf
DOI
10.1109/ICMTMA.2014.135
Filename
6802753
Link To Document