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Uncertainty Quantification of Parameters for Associated Risk to Human Health Due to Heavy Metal Content in Drinking Water using Possibility Theory: A Case Study in Ingestion

by Hrishikesh Boruah
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 186 - Number 67
Year of Publication: 2025
Authors: Hrishikesh Boruah
10.5120/ijca2025924480

Hrishikesh Boruah . Uncertainty Quantification of Parameters for Associated Risk to Human Health Due to Heavy Metal Content in Drinking Water using Possibility Theory: A Case Study in Ingestion. International Journal of Computer Applications. 186, 67 ( Feb 2025), 21-24. DOI=10.5120/ijca2025924480

@article{ 10.5120/ijca2025924480,
author = { Hrishikesh Boruah },
title = { Uncertainty Quantification of Parameters for Associated Risk to Human Health Due to Heavy Metal Content in Drinking Water using Possibility Theory: A Case Study in Ingestion },
journal = { International Journal of Computer Applications },
issue_date = { Feb 2025 },
volume = { 186 },
number = { 67 },
month = { Feb },
year = { 2025 },
issn = { 0975-8887 },
pages = { 21-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume186/number67/uncertainty-quantification-of-parameters-for-associated-risk-to-human-health-due-to-heavy-metal-content-in-drinking-water-using-possibility-theory-a-case-study-in-ingestion/ },
doi = { 10.5120/ijca2025924480 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2025-02-25T22:58:01.884586+05:30
%A Hrishikesh Boruah
%T Uncertainty Quantification of Parameters for Associated Risk to Human Health Due to Heavy Metal Content in Drinking Water using Possibility Theory: A Case Study in Ingestion
%J International Journal of Computer Applications
%@ 0975-8887
%V 186
%N 67
%P 21-24
%D 2025
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The main aim of risk assessment is to determine the potential detriment to human health from exposure to a substance or activity that under plausible circumstances can cause to human health. Risk assessment models involve inputs which may not be precisely known [7]. The uncertainty of the inputs gets propagated to the output risk. So, we need to quantify the uncertainty so as to be aware of the risk involved in any decision making process. Uncertainties can be modeled and analyzed using different theories, viz. Probability theory, Possibility theory, Evidence theory etc. Modeling of an uncertain parameter depends on the nature of the information available[1]. In this paper, I considered uncertainty quantification of parameters in the case of radiological risk assessment. I have analyzed the propagation of the risk in terms of Possibility theory (Fuzzy theory). Fuzzy method is discussed in this paper, taking the parameters of the input of the model as Fuzzy number. A case study is carried out with this method taking the parameters of the input as triangular Fuzzy Number.

References
  1. Baudrit, C., Dubois, D., Guyonnet, G., (2006) Joint Propagation and Exploitation of Probabilistic and Possibilistic Information in Risk Assessment, IEEE Transaction on Fuzzy Systems, vol. 14, no 5.
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  9. Shuai Zhang et al (2023): Human health risk assessment for contaminated sites: A retrospective review. Published by Elsevier Ltd.
Index Terms

Computer Science
Information Sciences

Keywords

Risk Assessment Uncertainty Variability Fuzzy number