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 :
بازگشت