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Multi-layer perceptron model for air quality prediction

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dc.citedby7
dc.contributor.authorAbdullah S.en_US
dc.contributor.authorIsmail M.en_US
dc.contributor.authorAhmed A.N.en_US
dc.contributor.authorid56509029800en_US
dc.contributor.authorid57210403363en_US
dc.contributor.authorid57214837520en_US
dc.date.accessioned2023-05-29T07:22:29Z
dc.date.available2023-05-29T07:22:29Z
dc.date.issued2019
dc.description.abstractThis study trained two MLP models with dierent activation functions in assessing the capability of the model for the prediction of air quality. The daily air quality data and meteorological variables from year 2010-2014 were assembled in training and testing the models. The MLP model with the combination of tansig and purelin activation function revealed 69.0% of variance in data with 5.58 ?g/m3 (RMSE) and 80.0% of variance in data with 8.14 ?g/m3 (RMSE), during training and testing phase, respectively. This model is appropriate for operational used by respected authorities in managing air quality and as early warning during unhealthy level of air quality. � 2019, Universiti Putra Malaysia.en_US
dc.description.natureFinalen_US
dc.identifier.epage95
dc.identifier.issueS
dc.identifier.scopus2-s2.0-85078661071
dc.identifier.spage85
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85078661071&partnerID=40&md5=32d4fa96a02de33e78449203a53b5e85
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/24261
dc.identifier.volume13
dc.publisherUniversiti Putra Malaysiaen_US
dc.sourceScopus
dc.sourcetitleMalaysian Journal of Mathematical Sciences
dc.titleMulti-layer perceptron model for air quality predictionen_US
dc.typeArticleen_US
dspace.entity.typePublication
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