Title :
A information method to recognize road traffic information based on Group of Neural Network
Author :
Yuejing, Lv ; Haixia, Zhang ; Xiangbo, Song ; Lei, Qin
Author_Institution :
Collge of Automhbile & Traffic Eng., Wuhan Univ. of Sci. & Technol., Wuhan, China
Abstract :
This paper, enlightened by the optic nerve of human, presents a method -- Group of Neural Network (GNN) to solve the problems when there are some problems in the information fusion of intelligent traffic road traffic information based on the Neural Network, and apply it to the road traffic information characteristic fusion to recognize the target. Compared with the neural network, the converge rate, the training time and the result and the stability of the recognition of the Neural Network in this new method can be increase improved. At last, through some road traffic information simulations; this method was validated by the realization of the traffic information detection based on the characteristic figure of the road traffic information. The intelligent traffic system vision navigation can recognize the traffic information according to the studied above.
Keywords :
neural nets; road traffic; GNN; group of Neural Network; information fusion; information method; intelligent traffic system vision navigation; road traffic information; traffic information detection; Group of Neural Network; Information fusion; Neural Network; Targets recognition; Traffic Information;
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
DOI :
10.1109/ICCASM.2010.5620101