Forecasting techniques for air pollution: utilizing Exponential Smoothing and ARIMA methods / Mohammad Nuzul Hakimi Mat Zain

Air pollution poses a significant threat to public health and the environment, necessitating the development of effective forecasting techniques to aid in pollution management and mitigation efforts. This study conducts a comparative analysis of two prominent time series forecasting methods, namely...

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Main Author:	Mat Zain, Mohammad Nuzul Hakimi
Format:	Thesis
Language:	English
Published:	2024
Subjects:	Analytical methods used in the solution of physical problems
Online Access:	https://ir.uitm.edu.my/id/eprint/95237/1/95237.pdf
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id	my-uitm-ir.95237
record_format	uketd_dc
spelling	my-uitm-ir.952372024-05-15T07:51:07Z Forecasting techniques for air pollution: utilizing Exponential Smoothing and ARIMA methods / Mohammad Nuzul Hakimi Mat Zain 2024 Mat Zain, Mohammad Nuzul Hakimi Analytical methods used in the solution of physical problems Air pollution poses a significant threat to public health and the environment, necessitating the development of effective forecasting techniques to aid in pollution management and mitigation efforts. This study conducts a comparative analysis of two prominent time series forecasting methods, namely Exponential Smoothing and Autoregressive Integrated Moving Average (ARIMA), to predict air pollution levels. The primary objective is to evaluate the performance and accuracy of these methods in capturing the dynamic and complex patterns inherent in air quality data.The findings reveal that, in this specific context, the Exponential Smoothing method, particularly Holt-Winters, consistently demonstrates a lower Root Mean Squared Error (RMSE) compared to ARIMA. This suggests that Holt-Winters Exponential Smoothing provides more accurate predictions for air pollution levels. 2024 Thesis https://ir.uitm.edu.my/id/eprint/95237/ https://ir.uitm.edu.my/id/eprint/95237/1/95237.pdf text en public degree Universiti Teknologi MARA, Terengganu College of Computing, Informatics and Mathematics Mat Ripin, Rohayati
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Mat Ripin, Rohayati
topic	Analytical methods used in the solution of physical problems
spellingShingle	Analytical methods used in the solution of physical problems Mat Zain, Mohammad Nuzul Hakimi Forecasting techniques for air pollution: utilizing Exponential Smoothing and ARIMA methods / Mohammad Nuzul Hakimi Mat Zain
description	Air pollution poses a significant threat to public health and the environment, necessitating the development of effective forecasting techniques to aid in pollution management and mitigation efforts. This study conducts a comparative analysis of two prominent time series forecasting methods, namely Exponential Smoothing and Autoregressive Integrated Moving Average (ARIMA), to predict air pollution levels. The primary objective is to evaluate the performance and accuracy of these methods in capturing the dynamic and complex patterns inherent in air quality data.The findings reveal that, in this specific context, the Exponential Smoothing method, particularly Holt-Winters, consistently demonstrates a lower Root Mean Squared Error (RMSE) compared to ARIMA. This suggests that Holt-Winters Exponential Smoothing provides more accurate predictions for air pollution levels.
format	Thesis
qualification_level	Bachelor degree
author	Mat Zain, Mohammad Nuzul Hakimi
author_facet	Mat Zain, Mohammad Nuzul Hakimi
author_sort	Mat Zain, Mohammad Nuzul Hakimi
title	Forecasting techniques for air pollution: utilizing Exponential Smoothing and ARIMA methods / Mohammad Nuzul Hakimi Mat Zain
title_short	Forecasting techniques for air pollution: utilizing Exponential Smoothing and ARIMA methods / Mohammad Nuzul Hakimi Mat Zain
title_full	Forecasting techniques for air pollution: utilizing Exponential Smoothing and ARIMA methods / Mohammad Nuzul Hakimi Mat Zain
title_fullStr	Forecasting techniques for air pollution: utilizing Exponential Smoothing and ARIMA methods / Mohammad Nuzul Hakimi Mat Zain
title_full_unstemmed	Forecasting techniques for air pollution: utilizing Exponential Smoothing and ARIMA methods / Mohammad Nuzul Hakimi Mat Zain
title_sort	forecasting techniques for air pollution: utilizing exponential smoothing and arima methods / mohammad nuzul hakimi mat zain
granting_institution	Universiti Teknologi MARA, Terengganu
granting_department	College of Computing, Informatics and Mathematics
publishDate	2024
url	https://ir.uitm.edu.my/id/eprint/95237/1/95237.pdf
_version_	1804889952445530112

Forecasting techniques for air pollution: utilizing Exponential Smoothing and ARIMA methods / Mohammad Nuzul Hakimi Mat Zain

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