Title :
Research on Traffic Flow Algorithm
Author_Institution :
Col. of Electr. & Informational Eng, Changsha Univ. of Sci. & Technol., Changsha, China
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;
Conference_Titel :
Measuring Technology and Mechatronics Automation (ICMTMA), 2014 Sixth International Conference on
Conference_Location :
Zhangjiajie
Print_ISBN :
978-1-4799-3434-8
DOI :
10.1109/ICMTMA.2014.135