Mathematical model of air quality index [AQI] in Peninsular Malaysia using support vector machine [SVM] / Nor Atikah Salleh

The presence of poisonous gases in the air is called air pollution. Malaysia is one of the developing countries strives towards development and industrialization. Air pollution is becoming a major environmental issue in Malaysia due to the increasing number of vehicles, open burning, release of chem...

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Main Author:	Salleh, Nor Atikah
Format:	Thesis
Language:	English
Published:	2019
Subjects:	Environmental conditions Environmental quality Environmental indicators Environmental degradation
Online Access:	https://ir.uitm.edu.my/id/eprint/25600/1/TD_NOR%20ATIKAH%20SALLEH%20CS%20R%2019.5.pdf
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id	my-uitm-ir.25600
record_format	uketd_dc
spelling	my-uitm-ir.256002019-09-19T08:16:43Z Mathematical model of air quality index [AQI] in Peninsular Malaysia using support vector machine [SVM] / Nor Atikah Salleh 2019-09-18 Salleh, Nor Atikah Environmental conditions. Environmental quality. Environmental indicators. Environmental degradation Mathematical statistics. Probabilities The presence of poisonous gases in the air is called air pollution. Malaysia is one of the developing countries strives towards development and industrialization. Air pollution is becoming a major environmental issue in Malaysia due to the increasing number of vehicles, open burning, release of chemical toxics from factories. All these air pollutants have a big impact on human health as it is reflected in the increase of hospital admissions particularly the respiratory, cardiovascular diseases and also to the surrounding environment. This study focused on the formulation of Cumulative Index (CI), comparative analysis of the proposed CI with the existing Air Quality Index (AQI) and classify the classes of CI. Monthly data of five air quality parameters which are Carbon dioxide (CO), Ozone (O3), Sulfur dioxide (SO2), Nitrogen dioxide (NO2), and Particular Matter less than 10 microns (PM10) in 37 monitoring stations for four years from 2013 to 2016 were gathered from Department of Environment (DOE). Microsoft Office Excel was used to run the AQI and CI. Thus, the Support Vector Machines (SVM) is proposed to classify CI. Classification classes are divided into two types which are good and harmful. This classification classes were derived from the helped by Rattle with R. The Radial Bias Function (RBF) is more accurate compared to Linear Function in order to classify the accuracy of the CI data. In a nutshell, from the research the classifier performs well to classify the quality of air. Hence, it can help the government sector to calculate the Cumulative Index by using a mathematical model. 2019-09 Thesis https://ir.uitm.edu.my/id/eprint/25600/ https://ir.uitm.edu.my/id/eprint/25600/1/TD_NOR%20ATIKAH%20SALLEH%20CS%20R%2019.5.pdf text en public degree Universiti Teknologi Mara Perlis Faculty of computer and mathematical sciences
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
topic	Environmental conditions Environmental quality Environmental indicators Environmental degradation Environmental conditions Environmental quality Environmental indicators Environmental degradation
spellingShingle	Environmental conditions Environmental quality Environmental indicators Environmental degradation Environmental conditions Environmental quality Environmental indicators Environmental degradation Salleh, Nor Atikah Mathematical model of air quality index [AQI] in Peninsular Malaysia using support vector machine [SVM] / Nor Atikah Salleh
description	The presence of poisonous gases in the air is called air pollution. Malaysia is one of the developing countries strives towards development and industrialization. Air pollution is becoming a major environmental issue in Malaysia due to the increasing number of vehicles, open burning, release of chemical toxics from factories. All these air pollutants have a big impact on human health as it is reflected in the increase of hospital admissions particularly the respiratory, cardiovascular diseases and also to the surrounding environment. This study focused on the formulation of Cumulative Index (CI), comparative analysis of the proposed CI with the existing Air Quality Index (AQI) and classify the classes of CI. Monthly data of five air quality parameters which are Carbon dioxide (CO), Ozone (O3), Sulfur dioxide (SO2), Nitrogen dioxide (NO2), and Particular Matter less than 10 microns (PM10) in 37 monitoring stations for four years from 2013 to 2016 were gathered from Department of Environment (DOE). Microsoft Office Excel was used to run the AQI and CI. Thus, the Support Vector Machines (SVM) is proposed to classify CI. Classification classes are divided into two types which are good and harmful. This classification classes were derived from the helped by Rattle with R. The Radial Bias Function (RBF) is more accurate compared to Linear Function in order to classify the accuracy of the CI data. In a nutshell, from the research the classifier performs well to classify the quality of air. Hence, it can help the government sector to calculate the Cumulative Index by using a mathematical model.
format	Thesis
qualification_level	Bachelor degree
author	Salleh, Nor Atikah
author_facet	Salleh, Nor Atikah
author_sort	Salleh, Nor Atikah
title	Mathematical model of air quality index [AQI] in Peninsular Malaysia using support vector machine [SVM] / Nor Atikah Salleh
title_short	Mathematical model of air quality index [AQI] in Peninsular Malaysia using support vector machine [SVM] / Nor Atikah Salleh
title_full	Mathematical model of air quality index [AQI] in Peninsular Malaysia using support vector machine [SVM] / Nor Atikah Salleh
title_fullStr	Mathematical model of air quality index [AQI] in Peninsular Malaysia using support vector machine [SVM] / Nor Atikah Salleh
title_full_unstemmed	Mathematical model of air quality index [AQI] in Peninsular Malaysia using support vector machine [SVM] / Nor Atikah Salleh
title_sort	mathematical model of air quality index [aqi] in peninsular malaysia using support vector machine [svm] / nor atikah salleh
granting_institution	Universiti Teknologi Mara Perlis
granting_department	Faculty of computer and mathematical sciences
publishDate	2019
url	https://ir.uitm.edu.my/id/eprint/25600/1/TD_NOR%20ATIKAH%20SALLEH%20CS%20R%2019.5.pdf
_version_	1783733863407681536

Mathematical model of air quality index [AQI] in Peninsular Malaysia using support vector machine [SVM] / Nor Atikah Salleh

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