An ANFIS Based Air Quality Model for Pre

This paper presents the results of an attempt to model sulfur dioxide (SO2) concentration in an urban area near a copper smelter in Bor, Serbia, using the Adaptive Neuro-Fuzzy Inference System (ANFIS) methodological approach. The primary objective was to develop a prediction tool capable of calculating potential SO2 concentrations that exceed prescribed limits based on various input parameters. The methodology involved the consideration of both technogenic and meteorological factors, specifically modeling the dependence of SO2 concentration as a function of wind speed, wind direction, air temperature, humidity, and the quantity of sulfur emitted from the pyrometallurgical process involved in sulfidic copper concentration treatment. The results illustrate the effectiveness of the ANFIS model in predicting SO2 levels, contributing valuable insights aimed at understanding pollution dynamics in urban settings. The findings are essential for informing local environmental management policies and ensuring compliance with air quality standards.