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Modeling the photocatalytic degradation of 1,2-Dihydroxybenzene using Multilayer Perceptron Neural Networks

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dc.contributor.authorAlsaffar M.A.en_US
dc.contributor.authorAyodele B.V.en_US
dc.contributor.authorAbdel Ghany M.A.en_US
dc.contributor.authorMustapa S.I.en_US
dc.contributor.authorid57210601717en_US
dc.contributor.authorid56862160400en_US
dc.contributor.authorid57215843327en_US
dc.contributor.authorid36651549700en_US
dc.date.accessioned2023-05-29T08:08:47Z
dc.date.available2023-05-29T08:08:47Z
dc.date.issued2020
dc.description.abstractIn this study, the modeling of photocatalytic degradation of 1,2 dihydroxybenzene using a multilayer perceptron neural network has been investigated. The multilayer perceptron neural network which consists of input layer, hidden layer with network configuration of 3, 17, 1 respectively were employed for predictive modeling using 20 datasets consisting the pH of the solution, the amount of the photocatalyst and the volume of the oxidant. The analysis of the network revealed that the volume of the oxidant was the most relevant factor that influences the degradation of the 1,2 dihydroxybenzene while the amount of photocatalyst has the least effect. The multilayer perceptron neural network model successfully predicts the photocatalytic degradation of the 1,2 dihydroxybenzene with coefficient of determination (R2) of 0.974. The predicted and the actual degradation of the 1,2 dihydroxybenzene was in close agreement with minimal error of prediction as indicated by the residual plot. This study has demonstrated the suitability of the multilayer perceptron neural network as a robust tool for modeling the prediction of 1,2 dihydroxybenzene degradation by photocatalytic process. � 2020 Institute of Physics Publishing. All rights reserved.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo12057
dc.identifier.doi10.1088/1757-899X/870/1/012057
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85089513864
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85089513864&doi=10.1088%2f1757-899X%2f870%2f1%2f012057&partnerID=40&md5=b066ad4896a6951e70fad71184485ed5
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/25384
dc.identifier.volume870
dc.publisherInstitute of Physics Publishingen_US
dc.relation.ispartofAll Open Access, Bronze
dc.sourceScopus
dc.sourcetitleIOP Conference Series: Materials Science and Engineering
dc.titleModeling the photocatalytic degradation of 1,2-Dihydroxybenzene using Multilayer Perceptron Neural Networksen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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