Classification of river water quality using multivariate analysis
The classification of river water quality is a useful way of reporting the water quality status of a river to control water pollution in monitored regions. The main objective of this study is to classify the water quality of the Muda River basin (Malaysia) using nine monitoring stations. This study...
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2015
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my.upm.eprints.478362016-07-13T04:33:36Z http://psasir.upm.edu.my/id/eprint/47836/ Classification of river water quality using multivariate analysis Azhar, Shah Christirani Aris, Ahmad Zaharin Yusoff, Mohd Kamil Ramli, Mohammad Firuz The classification of river water quality is a useful way of reporting the water quality status of a river to control water pollution in monitored regions. The main objective of this study is to classify the water quality of the Muda River basin (Malaysia) using nine monitoring stations. This study utilised multivariate analysis of cluster analysis (CA), principal component analysis (PCA) and discriminant analysis (DA). CA and PCA identified two different clusters (classes) that reflect the different water quality characteristics of the water systems. DA validated these clusters and produced a discriminant function (DF) that can predict the cluster membership of new samples. The classification generated by the multivariate analysis is consistent with those made by the Department of Environment (DOE). This study demonstrated that multivariate statistical techniques are effective for river water classification. Elsevier 2015 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/47836/1/47836.pdf Azhar, Shah Christirani and Aris, Ahmad Zaharin and Yusoff, Mohd Kamil and Ramli, Mohammad Firuz (2015) Classification of river water quality using multivariate analysis. Procedia Environmental Sciences, 30. pp. 79-84. ISSN 1878-0296 http://www.sciencedirect.com/science/article/pii/S1878029615006088 10.1016/j.proenv.2015.10.014 |
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The classification of river water quality is a useful way of reporting the water quality status of a river to control water pollution in monitored regions. The main objective of this study is to classify the water quality of the Muda River basin (Malaysia) using nine monitoring stations. This study utilised multivariate analysis of cluster analysis (CA), principal component analysis (PCA) and discriminant analysis (DA). CA and PCA identified two different clusters (classes) that reflect the different water quality characteristics of the water systems. DA validated these clusters and produced a discriminant function (DF) that can predict the cluster membership of new samples. The classification generated by the multivariate analysis is consistent with those made by the Department of Environment (DOE). This study demonstrated that multivariate statistical techniques are effective for river water classification. |
format |
Article |
author |
Azhar, Shah Christirani Aris, Ahmad Zaharin Yusoff, Mohd Kamil Ramli, Mohammad Firuz |
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Azhar, Shah Christirani Aris, Ahmad Zaharin Yusoff, Mohd Kamil Ramli, Mohammad Firuz Classification of river water quality using multivariate analysis |
author_facet |
Azhar, Shah Christirani Aris, Ahmad Zaharin Yusoff, Mohd Kamil Ramli, Mohammad Firuz |
author_sort |
Azhar, Shah Christirani |
title |
Classification of river water quality using multivariate analysis |
title_short |
Classification of river water quality using multivariate analysis |
title_full |
Classification of river water quality using multivariate analysis |
title_fullStr |
Classification of river water quality using multivariate analysis |
title_full_unstemmed |
Classification of river water quality using multivariate analysis |
title_sort |
classification of river water quality using multivariate analysis |
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Elsevier |
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2015 |
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http://psasir.upm.edu.my/id/eprint/47836/1/47836.pdf http://psasir.upm.edu.my/id/eprint/47836/ http://www.sciencedirect.com/science/article/pii/S1878029615006088 |
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