| Download | - View accepted manuscript: Interpreting drinking water quality in the distribution system using Dempster-Shafer theory of evidence (PDF, 743 KiB)
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| DOI | Resolve DOI: https://doi.org/10.1016/j.chemosphere.2004.11.087 |
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| Author | Search for: Sadiq, R.1; Search for: Rodriguez, M. J. |
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| Affiliation | - National Research Council of Canada. NRC Institute for Research in Construction
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| Format | Text, Article |
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| Subject | water quality; data fusion; theory of evidence; aggregation operators; water distribution system; Water quality |
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| Abstract | Interpreting water quality data routinely generated for control and monitoring purposes in water distribution systems is a complicated task for utility managers. In fact, data for diverse water quality indicators (physico-chemical and microbiological) are generated at different times and at different locations in the distribution system. To simplify and improve the understanding and the interpretation of water quality, methodologies for aggregation and fusion of data must be developed. In this paper, the Dempster-Shafer theory also called theory of evidence is introduced as a potential methodology for interpreting water quality data. The conceptual basis of this methodology and the process for its implementation are presented by two applications. The first application deals with the interpretation of spatial water quality data fusion, while the second application deals with the development of water quality index based on key monitored indicators. Based on the obtained results, the authors discuss the potential contribution of theory of evidence as a decision-making tool for water quality management. |
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| Publication date | 2005-04-01 |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| NRC number | NRCC 47672
NRC-IRC-16853 |
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| NPARC number | 20377015 |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | a2fbe1ef-6dcd-4a42-a74d-c10d37a65bb0 |
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| Record created | 2012-07-24 |
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| Record modified | 2020-04-07 |
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