Air quality prediction in Yinchuan by using neural networks

Abstract

A field study was carried out in Yinchuan to gather and evaluate information about the real environment. O 3 (Ozone), PM 10 (particle 10 um in diameter and smaller) and SO 2 (sulphur monoxide) constitute the major concern for air quality of Yinchuan. This paper addresses the problem of the predictions of such three pollutants by using the ANN. Because ANNs are non-linear mapping structure based on the function of the human brain. They have been shown to be universal and highly flexible function approximation for any date. These make powerful tools for models, especially when the underlying data relationship is unknown. © 2010 Springer-Verlag.