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Comparison of prediction model using spatial discriminant analysis for marine water quality index in mangrove estuarine zones

The prediction models of MWQI in mangrove and estuarine zones were constructed. The 2011–2015 data em- ployed in this study entailed 13 parameters from six monitoring stations in West Malaysia. Spatial discriminant analysis (SDA) had recommended seven significant parameters to develop the MWQI which...

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Main Authors:	Samsudin, Mohd Saiful, Azid, Azman, Khalit, Saiful Iskandar, Abdullah Sani, Muhamad Shirwan, Lananan, Fathurrahman
Format:	Article
Language:	English English English
Published:	Elsevier Ltd 2019
Subjects:	QA300 Analysis QD Chemistry
Online Access:	http://irep.iium.edu.my/71100/1/71100_Comparison%20of%20prediction%20model%20using%20spatial.pdf http://irep.iium.edu.my/71100/2/71100_Comparison%20of%20prediction%20model%20using%20spatial_SCOPUS.pdf http://irep.iium.edu.my/71100/13/71100_Comparison%20of%20prediction%20model%20using%20spatial_wos.pdf http://irep.iium.edu.my/71100/ https://www.sciencedirect.com/science/article/pii/S0025326X19301444
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spelling	my.iium.irep.711002020-04-10T02:47:32Z http://irep.iium.edu.my/71100/ Comparison of prediction model using spatial discriminant analysis for marine water quality index in mangrove estuarine zones Samsudin, Mohd Saiful Azid, Azman Khalit, Saiful Iskandar Abdullah Sani, Muhamad Shirwan Lananan, Fathurrahman QA300 Analysis QD Chemistry The prediction models of MWQI in mangrove and estuarine zones were constructed. The 2011–2015 data em- ployed in this study entailed 13 parameters from six monitoring stations in West Malaysia. Spatial discriminant analysis (SDA) had recommended seven significant parameters to develop the MWQI which were DO, TSS, O&G, PO4, Cd, Cr and Zn. These selected parameters were then used to develop prediction models for the MWQI using artificial neural network (ANN) and multiple linear regressions (MLR). The SDA-ANN model had higher R2 value for training (0.9044) and validation (0.7113) results than SDA-MLR model and was chosen as the best model in mangrove estuarine zone. The SDA-ANN model had also demonstrated lower RMSE (5.224) than the SDA-MLR (12.7755). In summary, this work suggested that ANN was an effective tool to compute the MWQ in mangrove estuarine zone and a powerful alternative prediction model as compared to the other modelling methods. Elsevier Ltd 2019-04-09 Article PeerReviewed application/pdf en http://irep.iium.edu.my/71100/1/71100_Comparison%20of%20prediction%20model%20using%20spatial.pdf application/pdf en http://irep.iium.edu.my/71100/2/71100_Comparison%20of%20prediction%20model%20using%20spatial_SCOPUS.pdf application/pdf en http://irep.iium.edu.my/71100/13/71100_Comparison%20of%20prediction%20model%20using%20spatial_wos.pdf Samsudin, Mohd Saiful and Azid, Azman and Khalit, Saiful Iskandar and Abdullah Sani, Muhamad Shirwan and Lananan, Fathurrahman (2019) Comparison of prediction model using spatial discriminant analysis for marine water quality index in mangrove estuarine zones. Marine Pollution Bulletin, 141. pp. 472-481. ISSN 0025-326X https://www.sciencedirect.com/science/article/pii/S0025326X19301444 10.1016/j.marpolbul.2019.02.045
institution	Universiti Islam Antarabangsa Malaysia
building	IIUM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	International Islamic University Malaysia
content_source	IIUM Repository (IREP)
url_provider	http://irep.iium.edu.my/
language	English English English
topic	QA300 Analysis QD Chemistry
spellingShingle	QA300 Analysis QD Chemistry Samsudin, Mohd Saiful Azid, Azman Khalit, Saiful Iskandar Abdullah Sani, Muhamad Shirwan Lananan, Fathurrahman Comparison of prediction model using spatial discriminant analysis for marine water quality index in mangrove estuarine zones
description	The prediction models of MWQI in mangrove and estuarine zones were constructed. The 2011–2015 data em- ployed in this study entailed 13 parameters from six monitoring stations in West Malaysia. Spatial discriminant analysis (SDA) had recommended seven significant parameters to develop the MWQI which were DO, TSS, O&G, PO4, Cd, Cr and Zn. These selected parameters were then used to develop prediction models for the MWQI using artificial neural network (ANN) and multiple linear regressions (MLR). The SDA-ANN model had higher R2 value for training (0.9044) and validation (0.7113) results than SDA-MLR model and was chosen as the best model in mangrove estuarine zone. The SDA-ANN model had also demonstrated lower RMSE (5.224) than the SDA-MLR (12.7755). In summary, this work suggested that ANN was an effective tool to compute the MWQ in mangrove estuarine zone and a powerful alternative prediction model as compared to the other modelling methods.
format	Article
author	Samsudin, Mohd Saiful Azid, Azman Khalit, Saiful Iskandar Abdullah Sani, Muhamad Shirwan Lananan, Fathurrahman
author_facet	Samsudin, Mohd Saiful Azid, Azman Khalit, Saiful Iskandar Abdullah Sani, Muhamad Shirwan Lananan, Fathurrahman
author_sort	Samsudin, Mohd Saiful
title	Comparison of prediction model using spatial discriminant analysis for marine water quality index in mangrove estuarine zones
title_short	Comparison of prediction model using spatial discriminant analysis for marine water quality index in mangrove estuarine zones
title_full	Comparison of prediction model using spatial discriminant analysis for marine water quality index in mangrove estuarine zones
title_fullStr	Comparison of prediction model using spatial discriminant analysis for marine water quality index in mangrove estuarine zones
title_full_unstemmed	Comparison of prediction model using spatial discriminant analysis for marine water quality index in mangrove estuarine zones
title_sort	comparison of prediction model using spatial discriminant analysis for marine water quality index in mangrove estuarine zones
publisher	Elsevier Ltd
publishDate	2019
url	http://irep.iium.edu.my/71100/1/71100_Comparison%20of%20prediction%20model%20using%20spatial.pdf http://irep.iium.edu.my/71100/2/71100_Comparison%20of%20prediction%20model%20using%20spatial_SCOPUS.pdf http://irep.iium.edu.my/71100/13/71100_Comparison%20of%20prediction%20model%20using%20spatial_wos.pdf http://irep.iium.edu.my/71100/ https://www.sciencedirect.com/science/article/pii/S0025326X19301444
_version_	1665894767504916480
score	13.211869

Comparison of prediction model using spatial discriminant analysis for marine water quality index in mangrove estuarine zones

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