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Feed-forward artificial neural network model for air pollutant index prediction in the Southern Region of Peninsular Malaysia

This paper describes the application of principal component analysis (PCA) and artificial neural network (ANN) to predict the air pollutant index (API) within the seven selected Malaysian air monitoring stations in the southern region of Peninsular Malaysia based on seven years database (2005-2011)...

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Main Authors: Azman, Azid, Hafizan, Juahir, Mohd Talib, Latif, Sharifuddin, Mohd Zain
格式: Article
語言:English
出版: 2013
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BL Religion
在線閱讀:http://eprints.unisza.edu.my/2880/1/FH02-ESERI-16-06619.pdf
http://eprints.unisza.edu.my/2880/
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spelling my-unisza-ir.28802021-10-04T03:49:03Z http://eprints.unisza.edu.my/2880/ Feed-forward artificial neural network model for air pollutant index prediction in the Southern Region of Peninsular Malaysia Azman, Azid Hafizan, Juahir Mohd Talib, Latif Sharifuddin, Mohd Zain BL Religion This paper describes the application of principal component analysis (PCA) and artificial neural network (ANN) to predict the air pollutant index (API) within the seven selected Malaysian air monitoring stations in the southern region of Peninsular Malaysia based on seven years database (2005-2011). Feed-forward ANN was used as a prediction method. The feed-forward ANN analysis demonstrated that the rotated principal component scores (RPCs) were the best input parameters to predict API. From the 4 RPCs, only 10 (CO, O3, PM10, NO2, CH4, NmHC, THC, wind direction, humidity and ambient temp) out of 12 prediction variables were the most significant parameters to predict API. The results proved that the ANN method can be applied successfully as tools for decision making and problem solving for better atmospheric management 2013-11 Article NonPeerReviewed text en http://eprints.unisza.edu.my/2880/1/FH02-ESERI-16-06619.pdf Azman, Azid and Hafizan, Juahir and Mohd Talib, Latif and Sharifuddin, Mohd Zain (2013) Feed-forward artificial neural network model for air pollutant index prediction in the Southern Region of Peninsular Malaysia. Journal of Environmental Protection, 4 (12). pp. 1-10. ISSN 2152-2197
institution Universiti Sultan Zainal Abidin
building UNISZA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Sultan Zainal Abidin
content_source UNISZA Institutional Repository
url_provider https://eprints.unisza.edu.my/
language English
topic BL Religion
spellingShingle BL Religion
Azman, Azid
Hafizan, Juahir
Mohd Talib, Latif
Sharifuddin, Mohd Zain
Feed-forward artificial neural network model for air pollutant index prediction in the Southern Region of Peninsular Malaysia
description This paper describes the application of principal component analysis (PCA) and artificial neural network (ANN) to predict the air pollutant index (API) within the seven selected Malaysian air monitoring stations in the southern region of Peninsular Malaysia based on seven years database (2005-2011). Feed-forward ANN was used as a prediction method. The feed-forward ANN analysis demonstrated that the rotated principal component scores (RPCs) were the best input parameters to predict API. From the 4 RPCs, only 10 (CO, O3, PM10, NO2, CH4, NmHC, THC, wind direction, humidity and ambient temp) out of 12 prediction variables were the most significant parameters to predict API. The results proved that the ANN method can be applied successfully as tools for decision making and problem solving for better atmospheric management
format Article
author Azman, Azid
Hafizan, Juahir
Mohd Talib, Latif
Sharifuddin, Mohd Zain
author_facet Azman, Azid
Hafizan, Juahir
Mohd Talib, Latif
Sharifuddin, Mohd Zain
author_sort Azman, Azid
title Feed-forward artificial neural network model for air pollutant index prediction in the Southern Region of Peninsular Malaysia
title_short Feed-forward artificial neural network model for air pollutant index prediction in the Southern Region of Peninsular Malaysia
title_full Feed-forward artificial neural network model for air pollutant index prediction in the Southern Region of Peninsular Malaysia
title_fullStr Feed-forward artificial neural network model for air pollutant index prediction in the Southern Region of Peninsular Malaysia
title_full_unstemmed Feed-forward artificial neural network model for air pollutant index prediction in the Southern Region of Peninsular Malaysia
title_sort feed-forward artificial neural network model for air pollutant index prediction in the southern region of peninsular malaysia
publishDate 2013
url http://eprints.unisza.edu.my/2880/1/FH02-ESERI-16-06619.pdf
http://eprints.unisza.edu.my/2880/
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score 13.251813

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