Soft Computing

, Volume 21, Issue 20, pp 6031–6041 | Cite as

Data-based multiple criteria decision-making model and visualized monitoring of urban drinking water quality

  • Weiwu Yan
  • Jialong Li
  • Manhua Liu
  • Xiaohui Bai
  • Huihe Shao
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Abstract

It is important to comprehensively evaluate and monitor urban drinking water quality to ensure a safe and clean drinking water supply. This paper discusses evaluating, analyzing and monitoring of urban drinking water quality and application systematically and proposes a multiple criteria decision-making model, which integrates analytic hierarchy process (AHP), Kullback–Leibler divergence ratio (KLDR) and comprehensive weighted index (CWI) method to evaluate the quality of drinking water comprehensively. AHP method and KLDR are employed to distribute reasonable weight to indices, and CWI method is used to get comprehensive score of multiple criteria system for evaluation. Association analysis is used to find the useful association rules between criteria and drinking water quality. Geographic information system (GIS) technology is employed to show the distribution map of drinking water quality visually. The proposed method is applied to real-time comprehensive evaluation and visualized monitoring of drinking water quality in Shanghai City. The distribution map of drinking water quality based on GIS can provide monitoring and government agencies with an overall assessment and enable them to make better informed decisions. Real-time application shows that the proposed methods are effective for the assessment and monitoring of urban water quality.

Keywords

Drinking water quality Kullback–Leibler divergence ratio AHP CWI Association analysis MCDM 

Notes

Acknowledgements

This work is sponsored by National Nature Science Foundation under Grant No. 60974119.

Funding    This study was funded by National Nature Science Foundation of China (NSFC) (60974119).

Compliance with ethical standards

Conflict of interest

Weiwu Yan has received research grants from NSFC. Jialong Li declares that he has no conflict of interest. Manhua Liu declares that he has no conflict of interest. Xiaohui Bai declares no conflict of interest. Huihe Shao declares no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Informed consent

Informed consent was obtained from all individual participants included in the study.

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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Weiwu Yan
    • 1
  • Jialong Li
    • 1
  • Manhua Liu
    • 2
  • Xiaohui Bai
    • 3
  • Huihe Shao
    • 1
  1. 1.Department of AutomationShanghai Jiao Tong UniversityShanghaiChina
  2. 2.Department of Instrument Science and TechnologyShanghai Jiao Tong UniversityShanghaiChina
  3. 3.School of Life Sciences and BiotechnologyShanghai Jiao Tong UniversityShanghaiChina

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