Methods to Improve the Generalization of BP Neural Network Applied in Air Pollution Forecasting

Atmospheric pollution prediction is helpful to find effective ways to control air pollution and improve air quality.BP neural network which was trained using Bayesian Regularization method and early stopping method was used to forecast the hourly concentration of PM_(2.5).The data of PM_(2.5) hourly concentration were obtained from monitoring site of Marylebone Road in London,UK.The prediction relative error goes from 20% to 49%.The results show that compared with networks which were trained using other methods, Bayesian Regularization method and early stopping method can improve the generalization ability of BP neural network.