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Water quality comprehensive evaluation method for large water distribution network based on clustering analysis

Chang, Kui and Jinliang, Gao and WU, Wenyan and Yixing, Yuan (2011) Water quality comprehensive evaluation method for large water distribution network based on clustering analysis. Journal of Hydroinformatics, 13 (3). pp. 390-400. ISSN 1464-7141

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Abstract or description

In order to evaluate water quality for a large water distribution network comprehensively, a two-stage classification method was used and the clustering methods, self-organizing map (SOM), K-means method and fuzzy c-mean (FCM), were represented. With these clustering methods, the pipes of a large real water distribution network were divided into some groups considering one or more water quality indicators synchronously. The water quality indicators of residual chlorine, water age, THMs, TAAs, TOC and BDOC are used in this paper. Residual chlorine and water age are two main water quality indicators. THMs and TAAs can represents the disinfection byproducts information. And TOC and BDOC are used to represents biological stability. According to the clustering results, the status of water quality of the water network was analysed. The results showed that the classification of SOM could express the comprehensive water quality in a water distribution network (WDN) directly and vividly by high-dimension water quality indicator projection to a low dimensional topology grid and that two-stage classification method has higher efficiency in comparison to the traditional clustering method. Water quality comprehensive evaluation was of significance for locating water quality monitoring, water network rehabilitation and expansion.

Item Type: Article
Uncontrolled Keywords: clustering analysis; fuzzy c-mean; K-means; self-organizing map; water distribution network; water quality evaluation
Subjects: G700 Artificial Intelligence
Faculty: Faculty of Arts and Creative Technologies > Art and Design
Related URLs:
Depositing User: Wenyan WU
Date Deposited: 15 Jan 2013 15:53
Last Modified: 19 Mar 2013 09:46
URI: http://eprints.staffs.ac.uk/id/eprint/302

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