A novel navigational risk analysis method using interval type-2 fuzzy sets

2018 ◽  
pp. 1689-1697
Author(s):  
C.L. Fan ◽  
D. Zhang ◽  
J.F. Zhang ◽  
H.J. Yao
Keyword(s):  
Risk Analysis ◽  
Fuzzy Sets ◽  
Analysis Method ◽  
Interval Type

A novel risk analysis approach for occupational safety using bayesian network and interval type-2 fuzzy sets: the case of underground mining

2021 ◽  
pp. 1-18
Author(s):  
Fatma Yaşli ◽  
Bersam Bolat
Keyword(s):  
Risk Analysis ◽  
Bayesian Network ◽  
Fuzzy Sets ◽  
Occupational Safety ◽  
Underground Mining ◽  
Computational Effort ◽  
Industrial Environment ◽  
Safety Risks ◽  
Interval Type

Occupational safety problems are no longer acceptable for any industrial environment. Lack of comprehensive and reliable evaluations for occupational safety causes many undesired events and harm to employees during the industrial process. In this study, it is aimed to develop an applicable risk analysis methodology for evaluating the undesired occupational events that occurred in the multi-process system where no historical accident records. The difficulty in obtaining and analyzing the data required for the determination of the occupational safety risks especially in the manually executed processes has been overcome with the Bayesian Network and interval type-2 fuzzy sets by using the expert judgments. While BN enables to development of a comprehensive reasoning approach about the occurrence of the events, interval type-2 fuzzy sets better represent the ambiguity in the judgments by covering the uncertainty in a wider mathematical range with less computational effort according to other fuzzy sets. During multi-processes in industrial activity, various occupational undesired events may occur, including rare events with very serious consequences or frequent events with very low severity consequences. To able to consider all kinds of events occurring in an industrial environment from a holistic risk perspective, a novel fuzzy scale for specifying the probability and consequence of the events are proposed by the interval type-2 fuzzy numbers. Therefore, all undesired events regard-less the probability and consequence which may occur during the multi-processes in a system and the main root causes of these events can be observed within the proposed methodology. A case study is used to emphasize the effect of the proposed methodology for risk analysis of occupational safety in underground mining. The results have indicated that occupational safety education is the most contributing factor to occurring the undesired occupational events in underground mining. We believe that this study could help evaluate the safety risk of the multi-process systems comprehensively and holistically and proposing strategic planning for mitigating the occupational safety risks.

scholarly journals Group Decision Analysis with Interval Type-2 Fuzzy Numbers

2017 ◽  
Vol 17 (1) ◽  
pp. 31-44 ◽  
Author(s):  
Galina Ilieva
Keyword(s):  
Decision Analysis ◽  
Fuzzy Sets ◽  
Business Intelligence ◽  
Fuzzy Numbers ◽  
Group Decision ◽  
Analysis Method ◽  
Interval Type ◽  
Benefits And Costs ◽  
Selection Of

Abstract This paper presentsagroup multi-criteria DEMATELand VIKORdecision analysis method with interval type-2 fuzzy sets. In order to compare normal fuzzy trapezoidal numbers, we convert them into crisp values using graded mean integration representation. Byacase study for selection of business intelligence platform, we prove that the proposed combination isafeasible solution that can work with benefits and costs criteria, while also reducing uncertainty in experts’assessments.

An interval type-2 hesitant fuzzy best-worst method

2021 ◽  
pp. 1-28
Author(s):  
Ashraf Norouzi ◽  
Hossein Razavi hajiagha
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Group Decision Making ◽  
Group Decision ◽  
Fuzzy Ahp ◽  
Uncertain Data ◽  
Interval Type ◽  
Best Worst Method

Multi criteria decision-making problems are usually encounter implicit, vague and uncertain data. Interval type-2 fuzzy sets (IT2FS) are widely used to develop various MCDM techniques especially for cases with uncertain linguistic approximation. However, there are few researches that extend IT2FS-based MCDM techniques into qualitative and group decision-making environment. The present study aims to adopt a combination of hesitant and interval type-2 fuzzy sets to develop an extension of Best-Worst method (BWM). The proposed approach provides a flexible and convenient way to depict the experts’ hesitant opinions especially in group decision-making context through a straightforward procedure. The proposed approach is called IT2HF-BWM. Some numerical case studies from literature have been used to provide illustrations about the feasibility and effectiveness of our proposed approach. Besides, a comparative analysis with an interval type-2 fuzzy AHP is carried out to evaluate the results of our proposed approach. In each case, the consistency ratio was calculated to determine the reliability of results. The findings imply that the proposed approach not only provides acceptable results but also outperforms the traditional BWM and its type-1 fuzzy extension.

Sign in / Sign up

Export Citation Format

Share Document