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
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;
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
DOI :
10.1109/CISE.2010.5677002