Characterization of water quality conditions in the Klang River Basin, Malaysia using self organizing map and K-means algorithm

Citation

Mohd Sharif, Sharifah and Mohd Kusin, Faradiella and Asha’ari, Zulfa Hanan and Aris, Ahmad Zaharin (2015) Characterization of water quality conditions in the Klang River Basin, Malaysia using self organizing map and K-means algorithm. Procedia Environmental Sciences, 30. pp. 73-78. ISSN 1878-0296

Abstract

This study aimed to determine the spatiotemporal pattern of the water quality data and identifying the sources of pollution in the Klang River Basin. The self organizing map (SOM) combined with the K-means algorithm arranged the data based on the relationships of 25 variables. The data from 2006 to 2009 for 30 monitoring stations were classified into six clusters. Water pollution in this river basin originated primarily from urban runoff, construction sites, faulty septic systems and industrial activities. The application of machine learning approaches is highly recommended to extract valuable information from the data for a holistic river basin management

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Additional Metadata

Item Type:	Article
Divisions:	Faculty of Environmental Studies
DOI Number:	https://doi.org/10.1016/j.proenv.2015.10.013
Publisher:	Elsevier
Keywords:	Water quality; Spatiotemporal pattern; Pollution sources; Machine learning; Self organizing map; K-means
Depositing User:	Mas Norain Hashim
Date Deposited:	03 May 2016 04:10
Last Modified:	03 May 2016 05:40
Altmetrics:	http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1016/j.proenv.2015.10.013
URI:	http://psasir.upm.edu.my/id/eprint/43196
Statistic Details:	View Download Statistic

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