DocumentCode
1876109
Title
Elman Neural Network Model of Traffic Flow Predicting in Mountain Expressway Tunnel
Author
Song, Xin-Sheng ; Li, Hui ; Wu, Bing-Hua ; Li, Ai-Zeng
Author_Institution
Dept. of Traffic Eng., Henan Univ. of Urban Constr., Pingdingshan, China
fYear
2010
fDate
10-12 Dec. 2010
Firstpage
1
Lastpage
4
Abstract
Aims at the complex and dynamic nature of traffic flow in mountain expressway tunnel, through the analysis of change characteristics of traffic flow, based on BP network improve the existing expressway traffic flow model, this thesis puts forward the Elman dynamic neural network model of traffic flow predicting in mountain expressway tunnel. In practice, this model has the strong operational, we adopt it to simulate and forecast the traffic flow of JingZhu expressway ShaoGuan section, reach the purpose of theory and reality unify. Through the analysis of the traffic flow characteristics this thesis could provide a viable research idea for the rational and orderly flowing of tunnel traffic flow.
Keywords
backpropagation; neural nets; traffic engineering computing; BP network; Elman dynamic neural network model; JingZhu expressway ShaoGuan section; expressway traffic flow model; mountain expressway tunnel; traffic flow forecasting; Analytical models; Artificial neural networks; Equations; Roads; Training; Vehicle dynamics; Vehicles;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Software Engineering (CiSE), 2010 International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-5391-7
Electronic_ISBN
978-1-4244-5392-4
Type
conf
DOI
10.1109/CISE.2010.5677002
Filename
5677002
Link To Document