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In this paper the back propagation (BP) neural network algorithm is applied to predict the traffic flow of urban road. The neuron structure needs 48 input nodes and 48 output nodes, so the frame of 48-20-48 is selected. First train an ideal input network with lower error square sum, then take the trained weight vector as initial value of the next input vector. The network training is realized by functions...
Realizing the shortcomings of VFCWA, we propose to establish Driving-Braking Behavior Model (DBBM), using BP neural network, to make VFCWA to fit with driver's behavior. And the tactic of combining DBBM and Security Model to form an effective VFCWA is proposed. Finally, through the simulation and experiment, it is proved that DBBM yield a satisfying result under the circumstances of straight path...
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