Interpreting drinking water quality in the distribution system using Dempster–Shafer theory of evidence

Sadiq, Rehan; Rodrı́guez, Manuel J.

doi:10.1016/j.chemosphere.2004.11.087

Cited by 33 publications

(15 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The applications of DS theory in civil and environmental engineering vary from slope stability (Binaghi et al, 1998), environmental decision-making (Attoh-Okine and Gibbons, 2001;Chang and Wright, 1996), seismic analysis (Alim, 1988), failure detection (Tanaka and Klir, 1999), construction management (Sönmez et al, 2002), water quality and water treatment (Sadiq and Rodriguez, 2005;Demotier et al, 2005;Boyd et al, 1993), pipe deterioration modeling (Najjaran et al, 2005), and remote sensing (Wang and Civco, 1994) to climate change (Luo and Caselton, 1997). Many more engineering applications of DS theory can be seen in detailed bibliography provided by Sentz and Ferson (2002).…”

Section: Dempster-shafer (Ds) Theorymentioning

confidence: 99%

Investigating evidential reasoning for the interpretation of microbial water quality in a distribution network

Sadiq

Najjaran

Kleiner

2006

Stoch Environ Res Ris Assess

Self Cite

View full text Add to dashboard Cite

/npsi/ctrl?lang=en http://nparc.cisti-icist.nrc-cnrc.gc.ca/npsi/ctrl?lang=fr Access and use of this website and the material on it are subject to the Terms and Conditions set forth at http://nparc.cisti-icist.nrc-cnrc.gc.ca/npsi/jsp/nparc_cp.jsp?lang=en NRC Publications Archive Archives des publications du CNRCThis publication could be one of several versions: author's original, accepted manuscript or the publisher's version. / La version de cette publication peut être l'une des suivantes : la version prépublication de l'auteur, la version acceptée du manuscrit ou la version de l'éditeur. For the publisher's version, please access the DOI link below./ Pour consulter la version de l'éditeur, utilisez le lien DOI ci-dessous.http://dx.doi.org/10.1007/s00477-006-0044-7Stochastic Environmental Research and Risk Assessment, 21, 1, pp. 63-73, 2006-11-01 Investigating evidential reasoning for the interpretation of microbial water quality in a distribution network Sadiq, R.; Najjaran, H.; Kleiner, Y.http://irc.nrc-cnrc.gc.ca I nve st igat ing evide nt ia l re a soning for t he int e rpre t at ion of m ic robia l w at e r qua lit y in a dist ribut ion ne t w ork NRCC-48316Sadiq, R.; Najjaran, H.; Kleiner, Y.A version of this document is published in / Une version de ce document se trouve dans: Stochastic Environmental Research and Risk Assessment, v. 21, no. 1, Nov. 2006, pp. 63-73 doi:10.1007 Investigating evidential reasoning for the interpretation of microbial water quality in distribution network * Rehan Sadiq, Homayoun Najjaran and Yehuda KleinerInstitute for Research in Construction, National Research Council, Ottawa, ON, Canada, K1A 0R6 AbstractTotal coliforms are used as indicators for evaluating microbial water quality in distribution network. However, total coliform provides only a weak 'evidence' of possible fecal contamination because pathogens are subset of total coliform and therefore their presence in drinking water do not necessarily mean fecal contamination. Heterotrophic plate counts, covers even a wider range of organisms and are also used commonly to evaluate microbial water quality in the distribution network. Both of these indicators provide incomplete and highly uncertain evidences individually, but the combination of evidence using data fusion may provide improved insight for interpreting microbial water quality in distribution network.The term data fusion refers to the synergistic aggregation of observations and measurements. Different attributes and inputs (e.g. various water quality indicators) can provide information on various aspects of a system or process by complementing each other. Complementary information and redundant data sets form the basis of data fusion applications in water quality monitoring and for condition assessment of infrastructure systems.Approximate reasoning methods like fuzzy logic and probabilistic reasoning are commonly employed for data fusion, where knowledge is uncertain (i.e., ambiguous, incomplete or vague). Within a probabilistic framework, traditionally infer...

show abstract

Section: Dempster-shafer (Ds) Theorymentioning

confidence: 99%

Investigating evidential reasoning for the interpretation of microbial water quality in a distribution network

Sadiq

Najjaran

Kleiner

2006

Stoch Environ Res Ris Assess

Self Cite

View full text Add to dashboard Cite

show abstract

“…The combination rule of D-S evidence theory can blend measures of evidence from multiple different sources [25,26]. Suppose m 1 , m 2 , .…”

Section: D-s Evidence Theorymentioning

confidence: 99%

Detection of water-quality contamination events based on multi-sensor fusion using an extented Dempster–Shafer method

Hou

Huang

et al. 2013

Meas. Sci. Technol.

View full text Add to dashboard Cite

This study presents a method for detecting contamination events of sources of drinking water based on the Dempster-Shafer (D-S) evidence theory. The detection method has the purpose of protecting water supply systems against accidental and intentional contamination events. This purpose is achieved by first predicting future water-quality parameters using an autoregressive (AR) model. The AR model predicts future water-quality parameters using recent measurements of these parameters made with automated (on-line) water-quality sensors. Next, a probabilistic method assigns probabilities to the time series of residuals formed by comparing predicted water-quality parameters with threshold values. Finally, the D-S fusion method searches for anomalous probabilities of the residuals and uses the result of that search to determine whether the current water quality is normal (that is, free of pollution) or contaminated. The D-S fusion method is extended and improved in this paper by weighted averaging of water-contamination evidence and by the analysis of the persistence of anomalous probabilities of water-quality parameters. The extended D-S fusion method makes determinations that have a high probability of being correct concerning whether or not a source of drinking water has been contaminated. This paper's method for detecting water-contamination events was tested with water-quality time series from automated (on-line) water quality sensors. In addition, a small-scale, experimental, water-pipe network was tested to detect water-contamination events. The two tests demonstrated that the extended D-S fusion method achieves a low false alarm rate and high probabilities of detecting water contamination events.

show abstract

“…The concept of D-S theory has been described in the various literature. Readers are suggested to consult with different D-S theorybased literature (e.g., Bicik et al 2011;Li 2007;Sadiq and Rodriguez 2005;Sadiq et al 2006) for the basic discussion and detail interpretation on the D-S theory.…”

Section: Dempster-shafer Theorymentioning

confidence: 99%

Integrated Decision Support System for Prognostic and Diagnostic Analyses of Water Distribution System Failures

Islam

Sadiq

Rodriguez

et al. 2016

Water Resour Manage

Self Cite

View full text Add to dashboard Cite

This paper presents an innovative decision support system (DSS) for prognostic and diagnostic analyses of water distribution system (WDS) failures. The framework of the DSS is based on four novel models developed and published by the authors of this paper. The four models include reliability assessment model, leakage potential model, leakage detection model, and water quality failure potential model. Information obtained from these models together with external information such as customer complaints, lab test results (if any), and historical information are integrated using Dempster-Shafer (D-S) theory to evaluate prognostic and diagnostic capabilities of the DSS. The prognostic capabilities of the DSS provide hydraulic and water quality states of a WDS whereas the diagnostic capabilities of the DSS help to identify the failure location with minimal time after the occurrence and will help to reduce false positive and false negative predictions. The framework has 'unique' capacity to bring the modeling information (hydraulic and Quality), consumer complaints, historical failure data, and laboratory test information under a single platform to perform a prognostic and diagnostic investigation of WDS failures (hydraulic and Quality). The proof of concept of the DSS has been demonstrated using data used in published four articles. The outcomes of this research widely addressed the uncertainties associated with WDS which improves the efficiency and effectiveness of diagnosis and prognosis analyses of WDS. It is expected that the developed integrated framework will help municipalities to make informed decisions to increase the safety, reliability and the security of public health.

show abstract

Interpreting drinking water quality in the distribution system using Dempster–Shafer theory of evidence

Cited by 33 publications

References 25 publications

Investigating evidential reasoning for the interpretation of microbial water quality in a distribution network

Investigating evidential reasoning for the interpretation of microbial water quality in a distribution network

Detection of water-quality contamination events based on multi-sensor fusion using an extented Dempster–Shafer method

Integrated Decision Support System for Prognostic and Diagnostic Analyses of Water Distribution System Failures

Contact Info

Product

Resources

About