- Tytuł:
- Prediction of industrial pollution by radial basis function networks
- Autorzy:
-
Djebbri, N.
Rouainia, M. - Powiązania:
- https://bibliotekanauki.pl/articles/207579.pdf
- Data publikacji:
- 2018
- Wydawca:
- Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
- Tematy:
-
forecasting
RBF
artificial neural network
pollution
prognozowanie
sztuczna sieć neuronowa
zanieczyszczenie - Opis:
- Atmospheric pollution has been receiving a significant interest for several decades since industries cause more and more pollution. Thanks to the development of many prediction techniques, scientists and industries are focusing more on pollution prediction. The aim of this work is to predict the two pollutant concentrations (NOx and CO) in industrial sites by a modified radial basis function (RBF) based neural network. The modification considered the spread parameter h of the activation function in the RBF network. In order to get the best network, the variations of this parameter for three cases were considered. In the first case, only pollutants concentrations variables were used, while in the second one, only the meteorological variables were utilized. In the third case, pollutants' concentrations were connected with meteorological variables. Based on calculation errors, the best model that ensures the best monitoring of pollutants concentration could be identified.
- Źródło:
-
Environment Protection Engineering; 2018, 44, 3; 153-164
0324-8828 - Pojawia się w:
- Environment Protection Engineering
- Dostawca treści:
- Biblioteka Nauki
Artykuł