Adaptive neuro-fuzzy based modelling for prediction of air pollution daily levels in city of Zonguldak.
Air pollution is a growing problem arising from domestic heating, high density of vehicle traffic, electricity production, and expanding commercial and industrial activities, all increasing in parallel with urban population. Monitoring and forecasting of air quality parameters in the urban area are important due to health impact. Artificial intelligent techniques are successfully used in modelling of highly complex and non-linear phenomena. In this study, adaptive neuro-fuzzy logic method has been proposed to estimate the impact of meteorological factors on SO2 and total suspended particular matter (TSP) pollution levels over an urban area. The model forecasts satisfactorily the trends in SO2 and TSP concentration levels, with performance between 75-90% and 69-80 %, respectively.
Yildirim
Yilmaz
Y
Zonguldak Karaelmas University, Department of Environmental Engineering, Incivez Street, 67100 Zonguldak, Turkey. yildirim61@yahoo.com
Bayramoglu
Mahmut
M
D000393:Air Pollutants / Q000032:analysis; D000397:Air Pollution; D002947:Cities; D004784:Environmental Monitoring / Q000379:methods; D017143:Fuzzy Logic; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D013458:Sulfur Dioxide / Q000032:analysis; D014421:Turkey
D000393:Air Pollutants; D013458:Sulfur Dioxide