Browsing by Author "Hazrul Abdul Hamid"

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    Boosted Regression Tree (BRT) Model for PM10 Concentrations Prediction in Malaysia
    (IOP Publishing, 2023) Norazrin; Hazrul Abdul Hamid; Ahmad Shukri Yahaya
    The aim of the study was to propose a Boosted Regression Tree (BRT) model for predicting PM10 concentrations in the short term. Multiple Linear Regression (MLR) and Boosted Regression Tree (BRT) models for short-term PM10 predictions are provided, and performance indicators (IA, R2, RMSE, MAE, and MAPE) are used to find the appropriate model. The Department of Environment Malaysia (DOE) provided seventeen years of daily average air quality monitoring data, including eight parameters (PM10, wind speed, temperature, relative humidity, NO2, SO2, CO, and O3) and five monitoring stations (Perai, Shah Alam, Nilai, Larkin, and Pasir Gudang).
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    Future daily PM10 concentrations prediction by combining regression models and feedforward backpropagation models with principle component analysis (PCA)
    (Elsevier, 2013) Ahmad Zia Ul-Saufie; Ahmad Shukri Yahaya; Nor Azam Ramli; Norrimi Rosaida; Hazrul Abdul Hamid
    Future PM10 concentration prediction is very important because it can help local authorities to enact preventative measures to reduce the impact of air pollution. The aims of this study are to improve prediction of Multiple Linear Regression (MLR) and Feedforward backpropagation (FFBP) by combining them with principle component analysis for predicting future (next day, next two-day and next three-day) PM10 concentration in Negeri Sembilan, Malaysia.