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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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 http://eprints.usm.my/52316/
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Institution:	Universiti Sains Malaysia
Language:	English

id	my.usm.eprints.52316
record_format	eprints
spelling	my.usm.eprints.52316 http://eprints.usm.my/52316/ PM10 Concentrations Short Term Prediction Using Regression, Artificial Neural Network And Hybrid Models 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 NonPeerReviewed application/pdf en http://eprints.usm.my/52316/1/Ahmad%20Zia%20Ul-Saufie.pdf%20cut.pdf Mohamad Japeri, Ahmad Zia Ul-Saufie (2013) PM10 Concentrations Short Term Prediction Using Regression, Artificial Neural Network And Hybrid Models. PhD thesis, Universiti Sains Malaysia.
institution	Universiti Sains Malaysia
building	Hamzah Sendut Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Sains Malaysia
content_source	USM Institutional Repository
url_provider	http://eprints.usm.my/
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
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
publishDate	2013
url	http://eprints.usm.my/52316/1/Ahmad%20Zia%20Ul-Saufie.pdf%20cut.pdf http://eprints.usm.my/52316/
_version_	1731226349986643968

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

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