Marija Savić, Ivan Mihajlović
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.
@article{e12fb4b0-f038-47da-b49e-d8f5f309f2ba,
title={An ANFIS Based Air Quality Model for Pre},
author={Marija Savić and Ivan Mihajlović},
year={2026},
language={en}
}TY - JOUR TI - An ANFIS Based Air Quality Model for Pre AU - Marija Savić AU - Ivan Mihajlović PY - 2026 LA - en ER -
Jirang Cui, Hans Jørgen Roven
Rapid growth in electronic equipment consumption has generated large quantities of electronic waste containing hazardous substances and high-value met
This paper addresses the challenge of assessing the feasibility of wind power plant projects at sites with insufficient or no local historic wind data
Important advances in electrochemical engineering technology over the last three decades have fostered the development of a lternative methods to alle