H. Wu, Y. Cong, G.Y. Jiang (PRC), and H.Y. Wang (USA)
ITS, Short-term Prediction, Traffic Flow, Neural Network, L-M algorithm
Traffic congestion affects greatly the further development of urban and travel of people. ITS can solve the serious traffic problem. Traffic parameters prediction is an important research item in the field of Intelligent Transportation Systems. In this paper, Short-term prediction methods of traffic flow based on Backpropagation (BP) neural network and L-M algorithm is proposed. Simulation results show that the performance is better than the general gradient-descent-based Algorithm.
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