The Comparative Study on Traffic Noise Prediction Model between Classical Algorithm and Neural Network Methods

Abstract

Traffic is the main noise source in urban environment, which has a significant impact on people's physical and mental health and labor productivity. To solve the problem of highway noise pollution, we should not only strengthen the prevention and control measures in the later stage but also scientifically and accurately predict and evaluate its noise impact in the early stage. The selection of the noise prediction model and the determination of its parameters is the necessary premise for the accurate prediction of highway noise. This paper introduces several traditional noise prediction algorithms based on statistical methods. Then the application of the artificial neural network method in traffic noise prediction is analyzed. The results show that artificial neural network is an effective noise prediction tool with high prediction accuracy. Compared with other statistical methods, the artificial neural network method has obvious advantages in traffic noise prediction.