Impact of the Factors on Building Neural Network Model on Air Pollution Forecast

This paper uses the data of hourly concentration of PM_2.5 in London and the traditional BP neural network to build forecast model and to quantitively forecast the hourly concentration of PM_2.5 in London, discusses the impacts of enlarging sample data, reducing noise of sample data and adding weather factors in inputing vector on setting up the model of the air pollution forecast network.Finally, it comes to the conclusion that properly selecting sample data and adding weather factors is beneficial to improving forecasting precision of the network model.