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Int. J. Environ. Res. Public Health 2016, 13(1), 115; doi:10.3390/ijerph13010115

Descriptive Characteristics of Surface Water Quality in Hong Kong by a Self-Organising Map

School of Economics and Management, Beihang University, Beijing 100191, China
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Author to whom correspondence should be addressed.
Academic Editor: Miklas Scholz
Received: 12 August 2015 / Revised: 18 December 2015 / Accepted: 31 December 2015 / Published: 8 January 2016
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Abstract

In this study, principal component analysis (PCA) and a self-organising map (SOM) were used to analyse a complex dataset obtained from the river water monitoring stations in the Tolo Harbor and Channel Water Control Zone (Hong Kong), covering the period of 2009–2011. PCA was initially applied to identify the principal components (PCs) among the nonlinear and complex surface water quality parameters. SOM followed PCA, and was implemented to analyze the complex relationships and behaviors of the parameters. The results reveal that PCA reduced the multidimensional parameters to four significant PCs which are combinations of the original ones. The positive and inverse relationships of the parameters were shown explicitly by pattern analysis in the component planes. It was found that PCA and SOM are efficient tools to capture and analyze the behavior of multivariable, complex, and nonlinear related surface water quality data. View Full-Text
Keywords: water quality; self-organising map; principal component analysis water quality; self-organising map; principal component analysis
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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An, Y.; Zou, Z.; Li, R. Descriptive Characteristics of Surface Water Quality in Hong Kong by a Self-Organising Map. Int. J. Environ. Res. Public Health 2016, 13, 115.

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