A Short-term Traffic Flow Forecasting Method Based on Chaos and RBF Neural network
Kaige Wen · Systems Engineering · 2007
Aiming at the prediction precision and real time problem using mathematical model for short-time traffic flow,from the point of nonlinear time sequence,this paper discussed short-time traffic flow prediction and presented a prediction method using RBF neural network based on chaos theory.On the premise that small data Lyapunav's exponent was used to decide that chaos exists in traffic flow system,we first performed phase space reconstruction for traffic flow data.RBF neural network was then constructed.Finally,we performed simulation using chaotic time sequence data generated by Lorenz and Rossler and the real measured expressway traffic flow data.Simulation results show that the proposed method has effective prediction results for simulated chaotic time sequence and highly prediction precision in short-time traffic flow.