A novel perspective on the selection of an effective approach to reduce road traffic accidents under Fermatean fuzzy settings

Road traffic accidents (RTAs) pose a significant hazard to the security of the general public, especially in developing nations. A daily average of more than three thousand fatalities is recorded worldwide, rating it as the second most prevalent cause of death among people aged 5-29. Precise and rel...

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Published in:PloS one 2024-05, Vol.19 (5), p.e0303139-e0303139
Main Authors: Alghazzawi, Dilshad, Noor, Aqsa, Alolaiyan, Hanan, Khalifa, Hamiden Abd El-Wahed, Alburaikan, Alhanouf, Xin, Qin, Razaq, Abdul
Format: Article
Language:English
Subjects:
Accidents
Accidents, Traffic - prevention & control
Ambiguity
Capital budgeting
COVID-19
COVID-19 diagnostic tests
Decision making
Developing countries
Disease transmission
Fuzzy algorithms
Fuzzy Logic
Fuzzy sets
Fuzzy systems
Humans
LDCs
Methods
Operators
Prevention
Quality management
Roads
Traffic
Traffic accidents
Traffic accidents & safety
Traffic engineering
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cited_by cdi_FETCH-LOGICAL-c637t-e5985f3290bc4763f4ce9b7bcf54744d583b7af699d71b927f1a1fed6520ec343
cites cdi_FETCH-LOGICAL-c637t-e5985f3290bc4763f4ce9b7bcf54744d583b7af699d71b927f1a1fed6520ec343
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creator Alghazzawi, Dilshad
Noor, Aqsa
Alolaiyan, Hanan
Khalifa, Hamiden Abd El-Wahed
Alburaikan, Alhanouf
Xin, Qin
Razaq, Abdul
description Road traffic accidents (RTAs) pose a significant hazard to the security of the general public, especially in developing nations. A daily average of more than three thousand fatalities is recorded worldwide, rating it as the second most prevalent cause of death among people aged 5-29. Precise and reliable decisionmaking techniques are essential for identifying the most effective approach to mitigate road traffic incidents. This research endeavors to investigate this specific concern. The Fermatean fuzzy set (FFS) is a strong and efficient method for addressing ambiguity, particularly when the concept of Pythagorean fuzzy set fails to provide a solution. This research presents two innovative aggregation operators: the Fermatean fuzzy ordered weighted averaging (FFOWA) operator and the Fermatean fuzzy dynamic ordered weighted geometric (FFOWG) operator. The salient characteristics of these operators are discussed and important exceptional scenarios are thoroughly delineated. Furthermore, by implementing the suggested operators, we develop a systematic approach to handle multiple attribute decisionmaking (MADM) scenarios that involve Fermatean fuzzy (FF) data. In order to show the viability of the developed method, we provide a numerical illustration encompassing the determination of the most effective approach to alleviate road traffic accidents. Lastly, we conduct a comparative evaluation of the proposed approach in relation to a number of established methodologies.
doi_str_mv 10.1371/journal.pone.0303139
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subjects Accidents
Accidents, Traffic - prevention & control
Ambiguity
Capital budgeting
COVID-19
COVID-19 diagnostic tests
Decision making
Developing countries
Disease transmission
Fuzzy algorithms
Fuzzy Logic
Fuzzy sets
Fuzzy systems
Humans
LDCs
Methods
Operators
Prevention
Quality management
Roads
Traffic
Traffic accidents
Traffic accidents & safety
Traffic engineering
title A novel perspective on the selection of an effective approach to reduce road traffic accidents under Fermatean fuzzy settings
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