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Neural Network Forecast for Daily Average PM10 Concentrations
Asian Journal of Chemistry,
Vol. 22 No. 1 (2010): Vol 22 Issue 1, 2010
Abstract
Over the past years, the health impact of particulate matter (PM)
has become a very current subject. In the environmental sciences a lot
of research effort goes towards the understanding of the particulate matter
phenomenon and the ability to forecast particulate matter concentrations.
The aim of the present work is to evaluate the potential of various developed
artificial neural network models to provide reliable predictions of
PM10 concentrations in Kayseri. Model structure obtained from air quality
monitoring network system performed by the Ministry of Environment
and Forestry was developed for 18 month data of Kayseri and the structure
was refined by Levenberg-Marquardt algorithm. Performance results
of artificial neural network models was compared with multiple regression
analysis and neural network give better predictions than multivariate
regression models.
has become a very current subject. In the environmental sciences a lot
of research effort goes towards the understanding of the particulate matter
phenomenon and the ability to forecast particulate matter concentrations.
The aim of the present work is to evaluate the potential of various developed
artificial neural network models to provide reliable predictions of
PM10 concentrations in Kayseri. Model structure obtained from air quality
monitoring network system performed by the Ministry of Environment
and Forestry was developed for 18 month data of Kayseri and the structure
was refined by Levenberg-Marquardt algorithm. Performance results
of artificial neural network models was compared with multiple regression
analysis and neural network give better predictions than multivariate
regression models.
Keywords
PM10
Ambient air
Air pollution forecast
Neural network model
Erciyes University.
OZKAN, O. (2009). Neural Network Forecast for Daily Average PM10 Concentrations. Asian Journal of Chemistry, 22(1), 582–588. Retrieved from https://asianpubs.org/index.php/ajchem/article/view/16680
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