Application of Artificial Neural Networks for Prediction of Air Pollution Levels in Environmental Monitoring

• Autorzy: Pawul M. , Śliwka M.

Identyfikatory

DOI

10.12911/22998993/64828

• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

environmental monitoring; air pollution; artificial neural networks; prediction

• Wydawca: Polskie Towarzystwo Inżynierii Ekologicznej ; Lublin University of Technology
• Czasopismo: Journal of Ecological Engineering
• Rocznik: 2016
• Tom: Vol. 17, nr 4
• Strony: 190--196
• Opis fizyczny: Bibliogr. 19 poz., tab., rys.

Twórcy

autor

Pawul M.

• AGH University of Science and Technology, Mickiewicza 30, 30-059 Krakow, Poland

autor

Śliwka M.

• AGH University of Science and Technology, Mickiewicza 30, 30-059 Krakow, Poland

Bibliografia

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Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.