Neural Network Forecast for Daily Average PM10 Concentrations - OZKAN, O. (Asian Journal of Chemistry, 2009)
Over the past years, the health impact of particulate matter (PM) has become a very current subject. In the environmental sciences a lot of research effort goes towards the understanding of the particulate matter phenomenon and the ability to forecast particulate matter concentrations. The aim of the present work is to evaluate the potential of various developed artificial neural network models to provide reliable predictions of PM10 concentrations in Kayseri. Model structure obtained from air quality monitoring network system performed by the Ministry of Environment and Forestry was developed for 18 month data of Kayseri and the structure was refined by Levenberg-Marquardt algorithm. Performance results of artificial neural network models was compared with multiple regression analysis and neural network give better predictions than multivariate regression models.