APPLICATION OF ARTIFICIAL NEURAL NETWORKS FOR PREDICTION OF AIR POLLUTION LEVELS IN ENVIRONMENTAL MONITORING
 
More details
Hide details
1
AGH University of Science and Technology, Mickiewicza 30 Av., 30-059 Kraków, Poland
CORRESPONDING AUTHOR
Małgorzata Pawul   

AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Krakow, Poland,, al. Mickiewicza 30, 30-059 Kraków, Poland
Publish date: 2016-09-30
 
J. Ecol. Eng. 2016; 17(4):190–196
KEYWORDS
TOPICS
ABSTRACT
Recently, a lot of attention was paid to the improvement of methods which are used to air quality forecasting. Artificial neural networks can be applied to model these problems. Their advantage is that they can solve the problem in the conditions of incomplete information, without the knowledge of the analytical relationship between the input and output data. In this paper we applied artificial neural networks to predict the PM 10 concentrations as factors determining the occurrence of smog phenomena. To create these networks we used meteorological data and concentrations of PM 10. The data were recorded in 2014 and 2015 at three measuring stations operating in Krakow under the State Environmental Monitoring. The best results were obtained by three-layer perceptron with back-propagation algorithm. The neural networks received a good fit in all cases.