PM10 Concentrations Short Term Prediction Using Regression, Artificial Neural Network And Hybrid Models

Particulate matter has significant effect to human health when the concentration level of this substance exceeds Malaysia Ambient Air Quality Guidelines. This research focused on particulate matter with aerodynamic diameter less than 10 11m, namely PMlO. Statistical modellings are required to predi...

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Bibliographic Details
Main Author:	Mohamad Japeri, Ahmad Zia Ul-Saufie
Format:	Thesis
Language:	English
Published:	2013
Subjects:	TD878-894 Special types of environment Including soil pollution, air pollution, noise pollution
Online Access:	http://eprints.usm.my/52316/1/Ahmad%20Zia%20Ul-Saufie.pdf%20cut.pdf
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id	my-usm-ep.52316
record_format	uketd_dc
spelling	my-usm-ep.523162022-04-13T09:31:44Z PM10 Concentrations Short Term Prediction Using Regression, Artificial Neural Network And Hybrid Models 2013-07 Mohamad Japeri, Ahmad Zia Ul-Saufie TD878-894 Special types of environment. Including soil pollution, air pollution, noise pollution Particulate matter has significant effect to human health when the concentration level of this substance exceeds Malaysia Ambient Air Quality Guidelines. This research focused on particulate matter with aerodynamic diameter less than 10 11m, namely PMlO. Statistical modellings are required to predict future PMlO concentrations. The aims of this study are to develop and predict future PMlO concentration for next day (D+ 1), next two-days (D+2) and next three days (D+3) in seven selected monitoring stations in Malaysia which are represented by fourth different types of land uses i.e. industrial (three sites), urban (three sites), a sub-urban site and a reference site. This study used daily average monitoring record from 2001 to 2010. 2013-07 Thesis http://eprints.usm.my/52316/ http://eprints.usm.my/52316/1/Ahmad%20Zia%20Ul-Saufie.pdf%20cut.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat Pengajian Kejuruteraan Awam
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
language	English
topic	TD878-894 Special types of environment Including soil pollution, air pollution, noise pollution
spellingShingle	TD878-894 Special types of environment Including soil pollution, air pollution, noise pollution Mohamad Japeri, Ahmad Zia Ul-Saufie PM10 Concentrations Short Term Prediction Using Regression, Artificial Neural Network And Hybrid Models
description	Particulate matter has significant effect to human health when the concentration level of this substance exceeds Malaysia Ambient Air Quality Guidelines. This research focused on particulate matter with aerodynamic diameter less than 10 11m, namely PMlO. Statistical modellings are required to predict future PMlO concentrations. The aims of this study are to develop and predict future PMlO concentration for next day (D+ 1), next two-days (D+2) and next three days (D+3) in seven selected monitoring stations in Malaysia which are represented by fourth different types of land uses i.e. industrial (three sites), urban (three sites), a sub-urban site and a reference site. This study used daily average monitoring record from 2001 to 2010.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Mohamad Japeri, Ahmad Zia Ul-Saufie
author_facet	Mohamad Japeri, Ahmad Zia Ul-Saufie
author_sort	Mohamad Japeri, Ahmad Zia Ul-Saufie
title	PM10 Concentrations Short Term Prediction Using Regression, Artificial Neural Network And Hybrid Models
title_short	PM10 Concentrations Short Term Prediction Using Regression, Artificial Neural Network And Hybrid Models
title_full	PM10 Concentrations Short Term Prediction Using Regression, Artificial Neural Network And Hybrid Models
title_fullStr	PM10 Concentrations Short Term Prediction Using Regression, Artificial Neural Network And Hybrid Models
title_full_unstemmed	PM10 Concentrations Short Term Prediction Using Regression, Artificial Neural Network And Hybrid Models
title_sort	pm10 concentrations short term prediction using regression, artificial neural network and hybrid models
granting_institution	Universiti Sains Malaysia
granting_department	Pusat Pengajian Kejuruteraan Awam
publishDate	2013
url	http://eprints.usm.my/52316/1/Ahmad%20Zia%20Ul-Saufie.pdf%20cut.pdf
_version_	1747822161800724480

PM10 Concentrations Short Term Prediction Using Regression, Artificial Neural Network And Hybrid Models

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