Abstract: The concentration prediction of the air pollutants is a complicated issue with nonlinear feature.Previous researches indicate that compared with the normal step wise regress method，the forecast precision with the ANN（Artificial Neural Networks） method is greatly improved.The GA_ANN air quality forecasting model is developed，which integrates Genetic Algorithm and Neural Network Algorithm.Genetic Algorithm is employed to select the most suitable forecasting factors for better performance. Some city air quality monitoring data and meteorological data from 2003 to 2006 are chosen to establish Neural Network of the GA_ANN model.The forecasting experiments about SO₂ and NO₂ of some city in 2007 show that the GA_ANN model has a higher forecasting precision than normal Neural Network model.