Object

Title: Prediction of industrial pollution by radial basis function networks

Creator:

Djebbri, Nadjet ; Rouainia, Mounira

Contributor:

Majewska-Nowak, Katarzyna Maria. Redakcja

Description:

Environment Protection Engineering. Vol. 44, 2018, nr 3, s. 153-164

Abstrakt:

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.

Publisher:

Oficyna Wydawnicza Politechniki Wrocławskiej

Place of publication:

Wrocław

Date:

2018

Resource Type:

artykuł

Resource Identifier:

doi:10.5277/epe180311 ; oai:dbc.wroc.pl:72321

Source:

<sygn. PWr A4232I> ; click here to follow the link ; click here to follow the link

Language:

eng

Relation:

Environment Protection Engineering ; Environment Protection Engineering. Vol. 44, 2018 ; Environment Protection Engineering. Vol. 44, 2018, nr 3

Rights:

Wszystkie prawa zastrzeżone (Copyright)

Access Rights:

Dla wszystkich w zakresie dozwolonego użytku

Location:

Politechnika Wrocławska

Group publication title:

Environment Protection Engineering

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