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HYBRID ANN AND FIREWORKS ALGORITHM FOR REAL-TIME SOFTWARE RELIABILITY PREDICTION

Ivy Botchway Felix Larbi Aryeh Boniface Kayode Alese
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A Comprehensive Review on the Application of Fuzzy Logic in Risk Analysis

by Stephy James, V.R. Renjith
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 186 - Number 54
Year of Publication: 2024
Authors: Stephy James, V.R. Renjith
10.5120/ijca2024924254

Stephy James, V.R. Renjith . A Comprehensive Review on the Application of Fuzzy Logic in Risk Analysis. International Journal of Computer Applications. 186, 54 ( Dec 2024), 16-38. DOI=10.5120/ijca2024924254

@article{ 10.5120/ijca2024924254,
author = { Stephy James, V.R. Renjith },
title = { A Comprehensive Review on the Application of Fuzzy Logic in Risk Analysis },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2024 },
volume = { 186 },
number = { 54 },
month = { Dec },
year = { 2024 },
issn = { 0975-8887 },
pages = { 16-38 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume186/number54/a-comprehensive-review-on-the-application-of-fuzzy-logic-in-risk-analysis/ },
doi = { 10.5120/ijca2024924254 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-12-27T02:45:35.320523+05:30
%A Stephy James
%A V.R. Renjith
%T A Comprehensive Review on the Application of Fuzzy Logic in Risk Analysis
%J International Journal of Computer Applications
%@ 0975-8887
%V 186
%N 54
%P 16-38
%D 2024
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Safety performance, together with productivity and quality, may be a primary objective for businesses looking to compete in the global scale in the innovative world of history. Every person has a right to safe, and that it is the duty of all sectors to work toward an accident-free workplace. Risk is defined as the probability that a potentially harmful event going to happen along with the intensity of any potential harm, damage, or loss. Major dangers and damages in particular have been managed through via means of statistical danger assessment techniques. a variety of techniques can be used to conduct risk assessments. Expert judgments are commonly employed to describe hazards since accurate data collected, which is typically needed for risk assessment, is frequently inaccessible in so many regions due to the lack of an accidents reporting system. Risks cannot, however, be compared because different evaluations by different specialists may produce different outcomes. Fuzzy logic analysis is one of the most crucial methods for reducing uncertainty and complexity in risk. This paper discusses fuzzy failure mode effect analysis (FFMEA), fuzzy failure mode effect analysis (FFTA), fuzzy Neural classifier (FBN), fuzzy failure mode effect assessment (FFMECA), fuzzy fault tree assessment (FETA), fuzzy failure mode effect assessment (FHAZOP), fuzzy key risks (FRM), fuzzy failure mode effect assessment (FLOPA) and additional hazy danger analytical methods like fuzzy Markov process and fuzzy Bow-Tie Assessment before discussing some of the uses of fuzzy set principle to risk analysis, explains the fundamentals of fuzzy principle.

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Index Terms

Computer Science
Information Sciences

Keywords

Network Risk analysis Bayesian network Fuzzy logic FTA FMEA

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