Introduction: Underground mining is considered one of the most hazardous industries and is often associated with serious work-related fatalities; this paper addresses job-related hazards and associated risks.
Method: A risk assessment approach is proposed (Pythagorean fuzzy environment) and a case study is carried out in an underground copper and zinc mine.
Results: Results of the study demonstrate that hazards can be categorized into different risk levels via compromised solutions of the fuzzy approach.
Conclusion: The study provides a theoretical contribution by suggesting a Pythagorean fuzzy numbers-based VlseKriterijumska Optimizacija I Kompromisno Resenje (PFVIKOR) approach. Moreover, it contributes to improving overall safety levels of underground mining by considering and advising on the potential hazards of risk management. Practical applications: The proposed approach will improve the existing safety risk assessment mechanism in underground copper and zinc mining.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.jsr.2019.03.005 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
An instructional emperor pigeon optimization (IEPO) based DeepEnrollNet for university student enrolment prediction and retention recommendation.
Sci Rep
December 2024
Department of Information Systems, College of Computer and Information Sciences, Majmaah University, Majmaah, 11952, Saudi Arabia.
Academic institutions face increasing challenges in predicting student enrollment and managing retention. A comprehensive strategy is required to track student progress, predict future course demand, and prevent student churn across various disciplines. Institutions need an effective method to predict student enrollment while addressing potential churn.
View Article and Find Full Text PDFA novel approach towards multiattribute decision making using q-rung orthopair fuzzy Dombi-Archimedean aggregation operators.
Heliyon
March 2024
Department of Mathematics, Abbottabad University of Science and Technology, Abbottabad, Khyber Pakhtunkhwa, 22500, Pakistan.
When dealing with real-life problems, the q-rung orthopair fuzzy set is a core concept because the power of the membership and non-membership degrees is less than or equal to one. The process of selecting and evaluating alternatives based on several criteria or characteristics is known as multi-attribute decision-making (MADM) problems. The overview of the attribute values is a significant problem in MADM.
View Article and Find Full Text PDFAddressing a decision problem through a bipolar Pythagorean fuzzy approach: A novel methodology applied to digital marketing.
Heliyon
February 2024
Centre of Mathematics, Universidade do Minho, Braga, Portugal.
Decision-making in real-world scenarios faces uncertainty. Fuzzy theory has been a means to represent such uncertainty. In this study, we propose an approach that incorporates bipolarity into multi-criteria decision-making processes applied to digital marketing.
View Article and Find Full Text PDFCorrigendum to "A multiple attribute group decision making model based on 2-tuple linguistic Pythagorean fuzzy Dombi aggregation operators for optimal selection of potential global suppliers" [Heliyon 10 (14) (July 2024) e34570].
Heliyon
October 2024
Department of Mathematics, College of Science, Qassim University, Buraydah, 51452, Saudi Arabia.
[This corrects the article DOI: 10.1016/j.heliyon.
View Article and Find Full Text PDFEnhancing readiness degree for Industrial Internet of Things adoption in manufacturing enterprises: An integrated Pythagorean fuzzy approach.
Heliyon
October 2024
The Cluster of Logistics and Rail Engineering, Faculty of Engineering, Mahidol University, Thailand.
This study proposes a hybrid multi-criteria decision-making (MCDM) methodology designed to enhance the readiness for adopting the Industrial Internet of Things (IIoT) in manufacturing enterprises. The Pythagorean fuzzy approach is employed to address uncertainty and imprecision throughout decision-making processes. The development framework in this study incorporates TOE (Technology-Organization-Environment) and HOT fit (Human-Organization-Technology) to pinpoint barriers to IIoT adoption.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!