Short-Term Forecasting of Traffic Flow Based on Genetic Algorithm and BP Neural Network

This paper focuses on the short-term traffic flow forecasting which plays an important role in traffic control and guidance system. To improve the efficiency and precision of short-term forecasting, the method of BP neural network optimized by genetic algorithm (GA) is put forward. Considering the shortcomings of traditional BP neural network, genetic algorithm is used to optimize the weight and threshold of BP neural network by training sample, then the optimized network is tested by testing sample and the network conducts short-term forecasting for 30 min by means of the rolling forecasting. The validity and accuracy of GA-BP forecasting model is tested on the basis of traffic flow. The simulation results demonstrate that the proposed model has higher superiority in convergence rate and forecasting precision.