Application of the first order of Markov chain model in describing the PM10 occurences in Shah Alam and Jerantut, Malaysia

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dc.contributor.authorMohamad, N. S.
dc.contributor.authorDeni, S. M.
dc.contributor.authorUl-Saufie, A. Z.
dc.coverage.publicationMalaysia
dc.date.accessioned2024-05-10T03:25:25Z
dc.date.available2024-05-10T03:25:25Z
dc.date.issued2018
dc.description.abstractPM10 has been identified as being a common problem in Malaysia and many other countries all over the world. A Markov chain probability model is found to fit the average daily PM10 concentrations data of urban station (Shah Alam) and background area station (Jerantut) in Malaysia. This study aims to identify the occurrence of polluted and non-polluted days affected by PM10 concentrations based on data for 12 years' period (2002-2013).
dc.identifier.citationMohamad, N. S., Deni, S. M., & Ul-Saufie, A. Z. (2018). Application of the First Order of Markov Chain Model in Describing the PM10 Occurrences in Shah Alam and Jerantut, Malaysia. Pertanika Journal of Science & Technology, 26(1).
dc.identifier.urihttps://repoemc.ukm.my/handle/123456789/559
dc.language.isoen
dc.publisherUniversiti Pertanian Malaysia Press
dc.publisher.alternativePertanika Journal of Science & Technology
dc.subjectMarkov chain model
dc.subjectPM10 concentrations
dc.subjectpolluted days
dc.subjectnon-polluted days
dc.subjectoccurrence
dc.titleApplication of the first order of Markov chain model in describing the PM10 occurences in Shah Alam and Jerantut, Malaysia
dc.typeJournal

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