DocumentCode
519749
Title
The short-term traffic flow prediction based on neural network
Author
Hu, Wusheng ; Liu, Yuanlin ; Li, Li ; Xin, Shujie
Author_Institution
Transp. Coll., Southeast Univ., Nanjing, China
Volume
1
fYear
2010
fDate
21-24 May 2010
Abstract
As we all know, to predict the short-term traffic flow accurately and efficiently is the premise and key of traffic management and control. Based on these existing study, this paper selected BP neural network model in which the traffic flow difference was taken as the input parameter, applied the thought of dynamic rolling prediction to design a new short-term traffic flow prediction method, and wrote the corresponding program. Then using the actual observation data of traffic flow presented the model structure, thought and calculation steps of this new method. The results show this method is feasibility, reliability, and of some practical value.
Keywords
backpropagation; neural nets; traffic engineering computing; BP neural network; short-term traffic flow prediction; traffic control; traffic management; Artificial neural networks; Communication system traffic control; Electronic mail; Neural networks; Prediction methods; Predictive models; Telecommunication traffic; Traffic control; Transportation; Vehicle dynamics; BP Algorithm; Dynamic Rolling Prediction; Neural Network; Short-term Traffic Flow;
fLanguage
English
Publisher
ieee
Conference_Titel
Future Computer and Communication (ICFCC), 2010 2nd International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-5821-9
Type
conf
DOI
10.1109/ICFCC.2010.5497785
Filename
5497785
Link To Document