15679

Risk Analysis using Fuzzy System based Risk Matrix Methodology

Article

Last updated: 03 Jan 2025

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Tags

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Abstract

this paper proposes a new risk assessment methodology using the fuzzy logic model based on the risk matrix information. The structure of the Fuzzy Inference System (FIS) formed in fuzzifier, knowledge base and defuzzifier. The input and output of the fuzzy system are simulated in crisp value. The proposed fuzzy model; and operator experiences were the devices for making the rules and inherent connection between variables in the fuzzy model. Fuzzy logic is one of the intelligence systems and it has wide range applications in fault analysis, event classification, accident analysis, safety and risk assessment. The structure of risk matrix reflects the shape of the membership functions and the If-Then rules of the fuzzy model design. The risk matrix is simulated in fuzzy approach to making it easier as a model based on If-Then rules. Simulation results investigated and illustrated that fuzzy logic system gives many advantages for risk assessment such as the dynamic modeling in If-Then rules.

DOI

10.21608/ajnsa.2018.2448.1047

Keywords

risk analysis, Risk matrix methodology, Fuzzy system applications in risk analysis

Authors

First Name

Magdy

Last Name

Zaky

MiddleName

Mahmoud

Affiliation

ETRR-2, EAEA, Egypt

Email

zaky_magdy@yahoo.com

City

Al-obour

Orcid

-

Volume

51

Article Issue

4

Related Issue

875

Issue Date

2018-10-01

Receive Date

2018-01-23

Publish Date

2018-10-02

Page Start

204

Page End

212

Print ISSN

1110-0451

Online ISSN

2090-4258

Link

https://ajnsa.journals.ekb.eg/article_15679.html

Detail API

https://ajnsa.journals.ekb.eg/service?article_code=15679

Order

22

Type

Original Article

Type Code

455

Publication Type

Journal

Publication Title

Arab Journal of Nuclear Sciences and Applications

Publication Link

https://ajnsa.journals.ekb.eg/

MainTitle

Risk Analysis using Fuzzy System based Risk Matrix Methodology

Details

Type

Article

Created At

22 Jan 2023