Application of artificial neural network in highway traffic volume prediction

Traffic is a complex system with great randomness and uncertainty. It is affected by a combination of many factors, including social, environmental and road factors. Therefore, the results of highway traffic forecasts are often unstable. In response to the above problems, a forecasting model based on artificial neural networks is proposed. The model is applied to traffic forecasting on the Xixian section of the Da-Guang Expressway in China, proving its stability and effectiveness. The application of artificial neural networks to predict the traffic volume of highways can greatly improve the efficiency and accuracy of traffic volume prediction. This is of great significance for solving the problem of road traffic congestion and improving the planning of highway network and regional development planning.