Traffic Flow Prediction Based on Hierarchical Genetic Optimized Algorithm

The forecast of short-term traffic flow in timely and accurate is one of important contents of intelligent transportation system research. Based on the related knowledge of wavelet analysis and fuzzy neural networks, this paper proposes the fuzzy wavelet neural networks control method. It takes wavelet function as fuzzy membership function, uses neural networks to realize fuzzy reasoning, and finishes the estimate of next cyclical traffic flow. Simultaneously the hierarchical genetic algorithm is used to optimize the network structure and the parameter. After the field data test, this method is high precise, stable and compatible.