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Real-time and accurate traffic flow forecasting is very important to the intelligent traffic guidance, control and management. According to the characteristics of traffic flow, this paper proposes a new model of traffic flow forecasting based on wavelet networks and the forecasting algorithm of comparable time intervals. The structures of wavelet networks are optimized with genetic algorithm. The experiment results show that this model is superior to the common BP neural networks in the aspects of flow forecasting precision and network convergence.