Prediction of the level of air pollution using principal component analysis and artificial neural network techniques: A case study in Malaysia

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dc.contributor.authorAzman Azid
dc.contributor.authorHafizan Juahir
dc.contributor.authorMohd Ekhwan Toriman
dc.contributor.authorMohd Khairul Amri Kamarudin
dc.contributor.authorAhmad Shakir Mohd Saudi
dc.contributor.authorChe Noraini Che Hasnam
dc.contributor.authorNor Azlina Abdul Aziz
dc.contributor.authorFazureen Azaman
dc.contributor.authorMohd Talib Latif
dc.contributor.authorSyahrir Farihan Mohamed Zainuddin
dc.contributor.authorMohamad Romizan Osman
dc.contributor.authorMohammad Yamin
dc.coverage.publicationMalaysia
dc.date.accessioned2024-05-10T03:25:41Z
dc.date.available2024-05-10T03:25:41Z
dc.date.issued2014
dc.description.abstractThis study focused on the pattern recognition of Malaysian air quality based on the data obtained from the Malaysian Department of Environment (DOE). Eight air quality parameters in ten monitoring stations in Malaysia for 7 years (2005-2011) were gathered. Principal component analysis (PCA) in the environmetric approach was used to identify the sources of pollution in the study locations. The combination of PCA and artificial neural networks (ANN) was developed to determine its predictive ability for the air pollutant index (API). The PCA has identified that CH4, NmHC, THC, O3, and PM10 are the most significant parameters.
dc.identifier.citationAzid, A., Juahir, H., Toriman, M. E., Kamarudin, M. K. A., Saudi, A. S. M., Hasnam, C. N. C., Aziz, N.A.A., Azaman, F., Latif, M.T., Zainuddin, S.F.M., Osman, M.R., & Yamin, M. (2014). Prediction of the level of air pollution using principal component analysis and artificial neural network techniques: A case study in Malaysia. Water, Air, & Soil Pollution, 225, 1-14.
dc.identifier.urihttps://repoemc.ukm.my/handle/123456789/602
dc.languageen
dc.publisherSpringer
dc.publisher.alternativeWater, Air and Soil Pollution
dc.subjectEnvironmetric
dc.subjectPattern recognition
dc.subjectPrincipal component analysis
dc.subjectArtificial neural network
dc.titlePrediction of the level of air pollution using principal component analysis and artificial neural network techniques: A case study in Malaysia
dc.typeJournal

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