| Research on contaminant sources identification of uncertainty water demand using genetic algorithm |
| Yan Xuesong ; Sun Jie; Hu Chengyu
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| 2017-06
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| 发表期刊 | CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
 |
| 卷号 | 20期号:2页码:1007-1016 |
| 摘要 | Urban water supply network is easily affected by intentional or occasional chemical and biological pollution, which threatens the health of consumers. In recent years, drinking water contamination happens occasionally, which seriously harms social stabilization and safety. Placing sensors in water supply pipes can monitor water quality in real time, which may prevent contamination accidents. However, how to reversely locate pollution sources through the detecting information from water quality sensors is a challengeable issue. Its difficulties lie in that limited sensors, massive pipe network nodes and dynamic water demand of users lead to the uncertainty, large-scale and dynamism of this optimization problem. This paper mainly studies the uncertainty problem in contaminant sources identification (CSI). The previous study of CSI supposes that hydraulic output (e.g., water demand) is known. Whereas, the inherent variability of urban water consumption brings an uncertain problem that water demand presents volatility. In this paper, the water demand of water supply network nodes simulated by Gaussian model is stochastic, and then being used to solve the problem of CSI, simulation-optimization method finds the minimum target of CSI and concentration which meet the simulation value and detected value of sensors. This paper proposes an improved genetic algorithm to solve the CSI problem under uncertainty water demand and comparative experiments are placed on two water distribution networks of different sizes. |
| 关键词 | Contaminant sources identification
Uncertainty water demand
Genetic algorithm
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| DOI | 10.1007/s10586-017-0787-6
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| 语种 | 英语
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| ISSN | 1386-7857
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| 收录类别 | SCI
; EI
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| EI入藏号 | 20170803382174
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| WOS记录号 | WOS:000403457100007
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| WOS类目 | Computer Science, Information Systems
; Computer Science, Theory & Methods
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| WOS研究方向 | Computer Science
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| 出版者 | SPRINGER
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| 引用统计 |
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| 文献类型 | 期刊论文
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| 条目标识符 | http://ir.cug.edu.cn/handle/2XU834YA/92077
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| 专题 | 教学院系_计算机学院
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| 通讯作者 | Hu Chengyu |
| 作者单位 | China Univ Geosci, Sch Comp Sci, Wuhan 430074, Hunan, Peoples R China
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推荐引用方式
GB/T 7714 |
Yan Xuesong,Sun Jie,Hu Chengyu. Research on contaminant sources identification of uncertainty water demand using genetic algorithm[J].
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS,2017,20(2):1007-1016.
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| APA |
Yan Xuesong,Sun Jie,&Hu Chengyu.(2017).Research on contaminant sources identification of uncertainty water demand using genetic algorithm.CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS,20(2),1007-1016.
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| MLA |
Yan Xuesong,et al."Research on contaminant sources identification of uncertainty water demand using genetic algorithm".CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 20.2(2017):1007-1016.
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