Design of BP neural network urban short-term traffic flow prediction software based on improved particle swarm optimization

With the acceleration of urbanization, the problem of urban traffic congestion has become more and more serious. Intelligent transportation system based on information technology is the most fundamental and effective measure to solve traffic congestion. The difficulty in the study of intelligent transportation technology lies in real-time and accurate short- term traffic flow prediction. In this paper, a short time traffic flow prediction software based on BP neural network is developed, which can be applied to the prediction of urban short-term traffic flow. Using this software can accurately and quickly predict the road traffic flow information at the next moment, which can provide powerful technical support for traffic control, traffic information service and traffic guidance of urban road traffic system, and alleviate the traffic pressure caused by the rapid development of urbanization. The software has important practical significance and application value in solving urban road traffic congestion and reducing environmental pollution.