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Modelling particulate matter (PM10) concentration in industrialized area: A comparative study of linear and nonlinear algorithms

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dc.citedby10
dc.contributor.authorAbdullah S.en_US
dc.contributor.authorIsmail M.en_US
dc.contributor.authorSamat N.N.A.en_US
dc.contributor.authorAhmed A.N.en_US
dc.contributor.authorid56509029800en_US
dc.contributor.authorid57210403363en_US
dc.contributor.authorid57204527316en_US
dc.contributor.authorid57214837520en_US
dc.date.accessioned2023-05-29T06:50:54Z
dc.date.available2023-05-29T06:50:54Z
dc.date.issued2018
dc.description.abstractParticulate matter is a critical air pollutant in Malaysia as it is the utmost dominant pollutant, especially in industrial and urban areas. The development of a robust model for PM10 concentration forecasting provides invaluable information for local authorities to take precautionary measures and implement significant actions to improve air pollution status. This study aims to develop and assess the linear (Multiple Linear Regression, MLR) and nonlinear (Multilayer Perceptron, MLP) models forecasting capability in industrial area of Pasir Gudang, Johor. Daily observations of PM10 concentration, meteorological factors (wind speed, ambient temperature and relative humidity) and gaseous pollutants (SO2, NO2 and CO) from the year 2007-2014 were used in this study. Results showed that MLP model was able to explain 68.7% (R2 = 0.687) variance in the data compared to MLR model with 52.7% (R2 = 0.527). Overall, the MLP model able to increase the accuracy of forecasting by 29.9% and reducing the error by 69.3% with respect to MLR model. Thus, it is proven that nonlinear model has high ability in virtually representing the complexity and nonlinearity of PM10 in the atmosphere without any prior assumptions, unlike the linear model. � 2006-2018 Asian Research Publishing Network (ARPN).en_US
dc.description.natureFinalen_US
dc.identifier.epage8235
dc.identifier.issue20
dc.identifier.scopus2-s2.0-85055946389
dc.identifier.spage8227
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85055946389&partnerID=40&md5=d04c764117d7efdc10a29f921288e3c3
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/23669
dc.identifier.volume13
dc.publisherAsian Research Publishing Networken_US
dc.sourceScopus
dc.sourcetitleARPN Journal of Engineering and Applied Sciences
dc.titleModelling particulate matter (PM10) concentration in industrialized area: A comparative study of linear and nonlinear algorithmsen_US
dc.typeArticleen_US
dspace.entity.typePublication
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