Discriminant analysis of water quality data in Langat River
River monitoring processes usually generate large databases of water quality variables. These water quality variables are important to identify the status of the river. Due to multidimensionality of complex characteristics in river water, meaningful information from a large database can be extracted...
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my.upm.eprints.558182017-06-30T09:44:51Z http://psasir.upm.edu.my/id/eprint/55818/ Discriminant analysis of water quality data in Langat River Mohd Ali, Zalina Ibrahim, Noor Akma Mengersen, Kerrie Shitan, Mahendran Juahir, Hafizan River monitoring processes usually generate large databases of water quality variables. These water quality variables are important to identify the status of the river. Due to multidimensionality of complex characteristics in river water, meaningful information from a large database can be extracted by using multivariate statistical methods, i.e., discriminant analysis (DA). Appropriate univariate transformation and data screening for multivariate outlier’s detection were considered. The DA approach used in this study gave better information on river water quality, especially concerning the contribution of the variables in discriminating between the three spatial areas in Langat River. Springer 2013 Conference or Workshop Item PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/55818/1/Discriminant%20analysis%20of%20water%20quality%20data%20in%20Langat%20River.pdf Mohd Ali, Zalina and Ibrahim, Noor Akma and Mengersen, Kerrie and Shitan, Mahendran and Juahir, Hafizan (2013) Discriminant analysis of water quality data in Langat River. In: International Conference on Environmental Forensics 2013, 11-14 Nov. 2013, Marriot Hotel, Putrajaya, Malaysia. (pp. 597-601). 10.1007/978-981-4560-70-2_106 |
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River monitoring processes usually generate large databases of water quality variables. These water quality variables are important to identify the status of the river. Due to multidimensionality of complex characteristics in river water, meaningful information from a large database can be extracted by using multivariate statistical methods, i.e., discriminant analysis (DA). Appropriate univariate transformation and data screening for multivariate outlier’s detection were considered. The DA approach used in this study gave better information on river water quality, especially concerning the contribution of the variables in discriminating between the three spatial areas in Langat River. |
format |
Conference or Workshop Item |
author |
Mohd Ali, Zalina Ibrahim, Noor Akma Mengersen, Kerrie Shitan, Mahendran Juahir, Hafizan |
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Mohd Ali, Zalina Ibrahim, Noor Akma Mengersen, Kerrie Shitan, Mahendran Juahir, Hafizan Discriminant analysis of water quality data in Langat River |
author_facet |
Mohd Ali, Zalina Ibrahim, Noor Akma Mengersen, Kerrie Shitan, Mahendran Juahir, Hafizan |
author_sort |
Mohd Ali, Zalina |
title |
Discriminant analysis of water quality data in Langat River |
title_short |
Discriminant analysis of water quality data in Langat River |
title_full |
Discriminant analysis of water quality data in Langat River |
title_fullStr |
Discriminant analysis of water quality data in Langat River |
title_full_unstemmed |
Discriminant analysis of water quality data in Langat River |
title_sort |
discriminant analysis of water quality data in langat river |
publisher |
Springer |
publishDate |
2013 |
url |
http://psasir.upm.edu.my/id/eprint/55818/1/Discriminant%20analysis%20of%20water%20quality%20data%20in%20Langat%20River.pdf http://psasir.upm.edu.my/id/eprint/55818/ |
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