Browsing by Author "Wan Nur Shaziayani"

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    A Review of PM10 Concentrations Modelling in Malaysia
    (IOP Publishing, 2020) Wan Nur Shaziayani; Ahmad Zia Ul-Saufie; Zuraira Libasin; Fuziatul Norsyiha Ahmad Shukri; Sharifah Sarimah Syed Abdullah; Norazian Mohamed Noor
    The purpose of predictive modelling is to predict the variable of interest with reasonable precision, and often to assess the contribution of the independent variables to the dependent variable. In this paper, all of the works examined are aimed at predicting concentrations of outdoor PM10 concentrations. The vast majority of the works reported used almost exclusively predictors of the meteorological and source emissions.
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    Coupling of quantile regression into boosted regression trees (BRT) technique in forecasting emission model of PM10 concentration
    (Springer, 2021) Wan Nur Shaziayani; Ahmad Zia Ul-Saufie; Hasfazilah Ahmat; Dhiya Al-Jumeily
    Air pollution is currently becoming a significant global environmental issue. The sources of air pollution in Malaysia are mobile or stationary. Motor vehicles are one of the mobile sources. Stationary sources originated from emissions caused by urban development, quarrying and power plants and petrochemical. The most noticeable contaminant in the Peninsular of Malaysia is the particulate matter (PM10), the highest contributor of Air Pollution Index (API) compared to other pollution parameters. The aim of this study is to determine the best loss function between quantile regression (QR) and ordinary least squares (OLS) using boosted regression tree (BRT) for the prediction of PM10 concentration in Alor Setar, Klang and Kota Bharu, Malaysia.