Fuzzy system reliability analysis using different types of intuitionistic fuzzy numbers

Author(s):  
Mohit Kumar ◽  
Shiv Prasad Yadav
2020 ◽  
Vol 24 (19) ◽  
pp. 14441-14448
Author(s):  
Mohammad Ghasem Akbari ◽  
Gholamreza Hesamian

Author(s):  
Pawan Kumar

The present study proposes to determine the fuzzy reliability of different systems in which the lifetime of components are following fuzzy exponential distribution where fuzzy reliability function and its α-cut set are presented. The fuzzy reliability of different systems is defined on the basis of octagonal intuitionistic fuzzy numbers. The fuzzy reliability functions of k-out-of-m system, series system, parallel systems, and their fuzzy mean time to failure are discussed respectively using the concept of α-cut of octagonal intuitionistic fuzzy numbers. Finally, some numerical examples are discussed to illustrate how to calculate the fuzzy system reliability and α-cut of fuzzy mean time to failure (FMTTF).


2021 ◽  
Vol 16 (1) ◽  
pp. 49-59
Author(s):  
Tjaša Šmidovnik ◽  
Petra Grošelj

Nowadays the multi-criteria decision making is very complicated due to uncertainty, vagueness, limited sources, knowledge and time. The Decision-making Trial and Evaluation Laboratory (DEMATEL) method is a widely used multi-criteria decision-making method to analyze the structure of a complex system. It is useful in analysing the cause and effect relationships between the components of the system. Fuzzy sets can be used to include uncertainty in multi-criteria decision making. Linguistic assessments of decision makers can be translated into fuzzy numbers. In this study, fuzzy numbers, intuitionistic fuzzy numbers and neutrosophic fuzzy numbers were used for the decision makers evaluations in the DEMATEL method. The aim of this study was to evaluate how different types of fuzzy numbers affect the final results. An application of risk in construction projects was selected from the literature, where seven experts used a linguistic scale to evaluate different criteria. The results showed that there are only slight differences between the weights of the criteria with regard to the type of fuzzy numbers.


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