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Article type: Research Article
Authors: Yan, Xuesonga | Zhao, Jinga | Hu, Chengyua | Wu, Qinghuab; c; *
Affiliations: [a] School of Computer Science, China University of Geosciences, Wuhan, Hubei, China | [b] Hubei Provincial Key Laboratory of Intelligent Robot, Wuhan Institute of Technology, Wuhan, Hubei, China | [c] School of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan, Hubei, China
Correspondence: [*] Corresponding author: Qinghua Wu, Hubei Provincial Key Laboratory of Intelligent Robot, Wuhan Institute of Technology, Wuhan, Hubei, China. Tel.: +86 18908632572; Fax: +86 027 67883716; E-mail:wuqinghua@sina.com
Abstract: In recent years, drinking water contamination incidents happen frequently, which is a serious threat to social stability and security. By placing the sensors for real-time monitoring of water quality in urban water supply, it can greatly reduce the probability of incidents of contamination. But how to use the information collected by water quality sensors to identify the contaminant source is a challenging problem. In this paper, we formulated the contaminant source identification problem into an optimization problem, and used hybrid encoding method to code the problem according to the properties of a variable, so as to improve the convergence speed and accuracy. We used different size of pipe network data in experiment, which results finally verified the validity and robustness of the proposed method.
Keywords: Water distribution network, contaminant source identification, optimization, genetic algorithm, hybrid encoding
DOI: 10.3233/JCM-160625
Journal: Journal of Computational Methods in Sciences and Engineering, vol. 16, no. 2, pp. 379-390, 2016
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