Prediction of Tehran Air Pollution Using PCA-ANFIS Method

Urban growth and increased use of vehicles have led to an increase in air pollution, especially in large and industrialized cities in recent years. Because of the adverse effect of air pollution on human and other creatures, prediction and modeling of this complex phenomenon have the main concern of researchers during the last years. The purpose of this research is to design an air pollution prediction system to identify the contaminated areas in order to help the urban managers and planners to control and reduce the amount of contaminants. In the proposed system in order to predict the air pollution in different seasons, PCA-ANFIS model has been used. In this system, meteorological data and concentrations of pollutants are used to predict air pollution in Tehran over the next 24 hours. In addition, spatial parameters including height, topography and distance from the road are used to model the spatial distribution of air pollution. Comparing the results of PCA-ANFIS and ANFIS methods prove that the proposed model obtained higher accuracy in less processing time.