Fusing probability density function into Dempster-Shafer theory of evidence for the evaluation of water treatment plant

Shakhawat Chowdhury*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

The evaluation of the status of a municipal drinking water treatment plant (WTP) is important. The evaluation depends on several factors, including, human health risks from disinfection by-products (R), disinfection performance (D), and cost (C) of water production and distribution. The Dempster-Shafer theory (DST) of evidence can combine the individual status with respect to R, D, and C to generate a new indicator, from which the overall status of a WTP can be evaluated. In the DST, the ranges of different factors affecting the overall status are divided into several segments. The basic probability assignments (BPA) for each segment of these factors are provided by multiple experts, which are then combined to obtain the overall status. In assigning the BPA, the experts use their individual judgments, which can impart subjective biases in the overall evaluation. In this research, an approach has been introduced to avoid the assignment of subjective BPA. The factors contributing to the overall status were characterized using the probability density functions (PDF). The cumulative probabilities for different segments of these factors were determined from the cumulative density function, which were then assigned as the BPA for these factors. A case study is presented to demonstrate the application of PDF in DST to evaluate a WTP, leading to the selection of the required level of upgradation for the WTP.

Original languageEnglish
Pages (from-to)3917-3929
Number of pages13
JournalEnvironmental Monitoring and Assessment
Volume185
Issue number5
DOIs
StatePublished - May 2013

Bibliographical note

Funding Information:
Acknowledgments The author would like to acknowledge the support provided by King Abdulaziz City for Science and Technology (KACST) through the Science and Technology Unit at King Fahd University of Petroleum and Minerals (KFUPM) for funding this work through project no. 10-WAT1398-04 as part of the National Science, Technology and Innovation Plan. The author also acknowledges the support from the provincial drinking water offices in Ontario and Quebec, Canada.

Keywords

  • Data combination
  • Dempster-Shafer theory
  • Probability density function

ASJC Scopus subject areas

  • General Environmental Science
  • Pollution
  • Management, Monitoring, Policy and Law

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