Neural networks for air pollution nowcasting

Abstract

This work illustrates the use and some results of artificial neural networks (ANNs) for data quality control of air pollutants. ANNs are applied to the short-term predicting of air pollutant concentrations in urban areas. Observed versus predicted data are compared to test the efficacy of ANNs in simulating environmental processes. Statistical analysis is used for choice of neural structure. The model is validated on original data.