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

Yan An, Zhihong Zou and Ranran Li
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Yan An: School of Economics and Management, Beihang University, Beijing 100191, China
Zhihong Zou: School of Economics and Management, Beihang University, Beijing 100191, China
Ranran Li: School of Economics and Management, Beihang University, Beijing 100191, China

IJERPH, 2016, vol. 13, issue 1, 1-13

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.

Keywords: water quality; self-organising map; principal component analysis (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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