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Reseach Article

Uncertainty Modeling in Risk Analysis: A Fuzzy Set Approach

by Palash Dutta, Tazid Ali
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 43 - Number 17
Year of Publication: 2012
Authors: Palash Dutta, Tazid Ali
10.5120/6199-8734

Palash Dutta, Tazid Ali . Uncertainty Modeling in Risk Analysis: A Fuzzy Set Approach. International Journal of Computer Applications. 43, 17 ( April 2012), 35-39. DOI=10.5120/6199-8734

@article{ 10.5120/6199-8734,
author = { Palash Dutta, Tazid Ali },
title = { Uncertainty Modeling in Risk Analysis: A Fuzzy Set Approach },
journal = { International Journal of Computer Applications },
issue_date = { April 2012 },
volume = { 43 },
number = { 17 },
month = { April },
year = { 2012 },
issn = { 0975-8887 },
pages = { 35-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume43/number17/6199-8734/ },
doi = { 10.5120/6199-8734 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:33:42.377267+05:30
%A Palash Dutta
%A Tazid Ali
%T Uncertainty Modeling in Risk Analysis: A Fuzzy Set Approach
%J International Journal of Computer Applications
%@ 0975-8887
%V 43
%N 17
%P 35-39
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Risk assessment is a popular and important tool in decision making process. Risk assessment is generally performed using models and model is a function of some parameters which are usually affected by uncertainty. Here, we consider that model parameters are affected by epistemic uncertainty. To represent epistemic uncertainty in general triangular fuzzy number or trapezoidal fuzzy numbers are used. In this paper, we study Gaussian fuzzy number to represent epistemic type uncertainty and try to fuse with triangular fuzzy numbers and also risk assessment is carried out under fuzzy environment.

References
  1. Bojadziev G. and Bojadziev, M. (1995). Fuzzy set, Fuzzy logic, application, (Singapore: world Scientific.)
  2. Dutta P., Boruah H. and Ali T. (2011). Fuzzy arithmetic with and without using -cut method: a comparative study”, International Journal of Latest Trends in Computing, vol-2, pp : 99-108.
  3. Pacheco M. A.C., Vellasco M .B. R.(2009) Intelligent Systems in Oil Field Development under Uncertainty. (Springer-Verlag, Berlin Heidelberg.)
  4. US EPA. 2001. Risk Assessment Guidance for Superfund, Volume I: Human Health Evaluation Manual (Part E, Supplemental Guidance for Dermal Risk Assessment). Office of Emergency and Remedial Response, EPA/540/R/99/005, Interim, Review Draft. United States Environmental Protection Agency. September 2001.
Index Terms

Computer Science
Information Sciences

Keywords

Risk Assessment Epistemic Uncertainty Gaussian Fuzzy Number