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Risk assessment of firefighting job using hybrid SWARA-ARAS methods in fuzzy environment

Identification and risk assessment of hazards using classic methods have various flaws, such as ambiguity and uncertainty in the data, inability to correctly reflect the human thinking style, failure to assign weight to criteria, use of predetermined data and tables, and the evaluator's role in...

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Detalles Bibliográficos
Autores principales: Soltani, Edris, Mirzaei Aliabadi, Mostafa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10694163/
http://dx.doi.org/10.1016/j.heliyon.2023.e22230
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author Soltani, Edris
Mirzaei Aliabadi, Mostafa
author_facet Soltani, Edris
Mirzaei Aliabadi, Mostafa
author_sort Soltani, Edris
collection PubMed
description Identification and risk assessment of hazards using classic methods have various flaws, such as ambiguity and uncertainty in the data, inability to correctly reflect the human thinking style, failure to assign weight to criteria, use of predetermined data and tables, and the evaluator's role in the results of the risk assessment process. Therefore, developing these methods and creating approaches with higher accuracy and sensitivity is necessary. This study utilized a developed method that integrated SWARA's weighting methods and ARAS prioritization using Fine-Kinney criteria in a fuzzy environment to evaluate the risks of the firefighting job. The sensitivity analysis results confirmed the accuracy and applicability of the proposed method. Based on the study's results, the inhalation of harmful gases and smoke (R3) was identified as the most critical risk, while concern about the optimal operation (R21) was considered the least dangerous risk in firefighting.
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spelling pubmed-106941632023-12-05 Risk assessment of firefighting job using hybrid SWARA-ARAS methods in fuzzy environment Soltani, Edris Mirzaei Aliabadi, Mostafa Heliyon Research Article Identification and risk assessment of hazards using classic methods have various flaws, such as ambiguity and uncertainty in the data, inability to correctly reflect the human thinking style, failure to assign weight to criteria, use of predetermined data and tables, and the evaluator's role in the results of the risk assessment process. Therefore, developing these methods and creating approaches with higher accuracy and sensitivity is necessary. This study utilized a developed method that integrated SWARA's weighting methods and ARAS prioritization using Fine-Kinney criteria in a fuzzy environment to evaluate the risks of the firefighting job. The sensitivity analysis results confirmed the accuracy and applicability of the proposed method. Based on the study's results, the inhalation of harmful gases and smoke (R3) was identified as the most critical risk, while concern about the optimal operation (R21) was considered the least dangerous risk in firefighting. Elsevier 2023-11-11 /pmc/articles/PMC10694163/ http://dx.doi.org/10.1016/j.heliyon.2023.e22230 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research Article
Soltani, Edris
Mirzaei Aliabadi, Mostafa
Risk assessment of firefighting job using hybrid SWARA-ARAS methods in fuzzy environment
title Risk assessment of firefighting job using hybrid SWARA-ARAS methods in fuzzy environment
title_full Risk assessment of firefighting job using hybrid SWARA-ARAS methods in fuzzy environment
title_fullStr Risk assessment of firefighting job using hybrid SWARA-ARAS methods in fuzzy environment
title_full_unstemmed Risk assessment of firefighting job using hybrid SWARA-ARAS methods in fuzzy environment
title_short Risk assessment of firefighting job using hybrid SWARA-ARAS methods in fuzzy environment
title_sort risk assessment of firefighting job using hybrid swara-aras methods in fuzzy environment
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10694163/
http://dx.doi.org/10.1016/j.heliyon.2023.e22230
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