Research on urban traffic flow lntelligent prediction based on artificial neural network
Yuan Luo
Abstract
Yuan Luo
Abstract
By analying the current situation of the urban traffic system,this paper expounds the relationship between traffic congestion and the traffic flow,and shows that it's very important to make the traffic flow prediction of the urban traffic system. Nowadays, some types of artificial neural network models are used in the urban traffic flow prediction, such as linear network, back propagation and feedback network. In this paper, the linear network model is mainly used to analyze the traffic flow prediction, which is simple in the construction, easy in the application, quick in the response and strong in the real time. The urban traffic flow prediction is simulated under the particular situation,and the result of the simulation shows that the Linear Network shown in this paper can fit the urban traffic flow prediction very well.
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By analying the current situation of the urban traffic system,this paper expounds the relationship between traffic congestion and the traffic flow,and shows that it's very important to make the traffic flow prediction of the urban traffic system. Nowadays, some types of artificial neural network models are used in the urban traffic flow prediction, such as linear network, back propagation and feedback network. In this paper, the linear network model is mainly used to analyze the traffic flow prediction, which is simple in the construction, easy in the application, quick in the response and strong in the real time. The urban traffic flow prediction is simulated under the particular situation,and the result of the simulation shows that the Linear Network shown in this paper can fit the urban traffic flow prediction very well.
Key concepts: Traffic flow (computer networking), Traffic generation model, Computer science, Artificial neural network, Network traffic simulation, Traffic congestion reconstruction with Kerner's three-phase theory, Traffic congestion, Flow (mathematics)