Conception and Implementation of a New Data-Driven Fuzzy Method for Reliability and Safety Analysis

2020 ◽  
Vol 16 (03) ◽  
pp. 517-539
Author(s):  
F. Abbasi ◽  
T. Allahviranloo
Keyword(s):  
System Reliability ◽  
Fuzzy Number ◽  
Fuzzy System ◽  
Fuzzy Systems ◽  
Fuzzy Numbers ◽  
Accurate Estimate ◽  
Data Driven ◽  
Proposed Model ◽  
Parameters Uncertainty ◽  
New Type

In this paper, the probability of failure of the components is introduced as a new type of fuzzy numbers called Gaussian patchy fuzzy number to insert parameters’ uncertainty. The reason for the use of such fuzzy numbers is also due to their realistic estimation. Hence, in order to obtain a more accurate estimate of each failure occurrence and overall system reliability analysis, we assume that the fundamental events of fault tree are in the form of Gaussian patchy fuzzy number on [0, 1], and then, by applying the fuzzy transmission average (TA) [F. Abbasi, T. Allahviranloo and S. Abbasbandy, A new attitude coupled with fuzzy thinking to fuzzy rings and fields, Journal of Intelligent and Fuzzy Systems, 29 (2015) 851-861], we will model the reliability of the fuzzy system (especially the series and the parallel). Applying such fuzzy operations and numbers will lead to a more realistic analysis of the reliability of the fuzzy system. Finally, the proposed model has been used for the lack of satisfaction of the University’s administrative and financial assistant.

Conception and Implementation of a New Data-Driven Fuzzy Method for Reliability and Safety Analysis

2020 ◽  
Vol 16 (02) ◽  
pp. 339-361
Author(s):  
F. Abbasi ◽  
T. Allahviranloo
Keyword(s):  
System Reliability ◽  
Fuzzy Number ◽  
Fuzzy System ◽  
Fuzzy Systems ◽  
Fuzzy Numbers ◽  
Accurate Estimate ◽  
Data Driven ◽  
Proposed Model ◽  
Parameters Uncertainty ◽  
New Type

In this paper, the probability of failure of the components is introduced as a new type of fuzzy number called Gaussian patchy fuzzy number to insert parameters’ uncertainty. The reason for the use of such fuzzy numbers is also due to their realistic estimation. Hence, in order to obtain a more accurate estimate of each failure occurrence and overall system reliability analysis, we assume that the fundamental events of fault tree are in the form of Gaussian patchy fuzzy number on [0, 1], and then, by applying the fuzzy transmission average (TA) [F. Abbasi, T. Allahviranloo and S. Abbasbandy, A new attitude coupled with fuzzy thinking to fuzzy rings and fields, Journal of Intelligent and Fuzzy Systems 29 (2015) 851–861.], we will model the reliability of the fuzzy system (especially the series and the parallel). Applying such fuzzy operations and numbers will lead to a more realistic analysis of the reliability of the fuzzy system. Finally, the proposed model has been used for the lack of satisfaction of the University’s administrative and financial assistant.

Fuzzy Reliability of an Imprecise Failure to Start of an Automobile Using Pseudo-Parabolic Fuzzy Numbers

2018 ◽  
Vol 14 (03) ◽  
pp. 323-341 ◽  
Author(s):  
F. Abbasi
Keyword(s):  
Fuzzy Systems ◽  
Fuzzy Numbers ◽  
Extension Principle ◽  
Fuzzy Arithmetic ◽  
Fuzzy Reliability ◽  
Fuzzy Environment ◽  
Distributed Components ◽  
Proposed Model ◽  
New Type ◽  
The Membership Function

In this paper, we propose the notion of pseudo-parabolic fuzzy numbers and the component failure probabilities are considered as a new type of fuzzy number as pseudo-parabolic to incorporate the uncertainties in the parameter, due to a more realistic estimate of them. Then, we analyze the reliability of fuzzy system (particularly, series and parallel system) with independent and non-identically distributed components, and using the new operations of TA [F. Abbasi et al., Journal of Intelligent and Fuzzy Systems 29 (2015) 851–861], due to the smaller results support, easier calculations and special properties than fuzzy arithmetic operations based on the extension principle (in the domain of the membership function) and the interval arithmetic (in the domain of the [Formula: see text]-cuts). We provide a more realistic fuzzy reliability analysis. Finally, an imprecise failure to start of an automobile is considered in fuzzy environment. The reliability of components of the proposed model is considered as pseudo-parabolic fuzzy numbers.

scholarly journals A New Data-Driven Control System for MEMSs Gyroscopes: Dynamics Estimation by Type-3 Fuzzy Systems

Micromachines ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1390
Author(s):  
Khalid A. Alattas ◽  
Ardashir Mohammadzadeh ◽  
Saleh Mobayen ◽  
Ayman A. Aly ◽  
Bassem F. Felemban ◽  
...  
Keyword(s):  
Fuzzy System ◽  
Measurement Errors ◽  
Fuzzy Systems ◽  
Data Driven ◽  
Output Data ◽  
Data Set ◽  
Control Scheme ◽  
Mems Gyroscopes ◽  
The Stability ◽  
Type 3

In this study, a novel data-driven control scheme is presented for MEMS gyroscopes (MEMS-Gs). The uncertainties are tackled by suggested type-3 fuzzy system with non-singleton fuzzification (NT3FS). Besides the dynamics uncertainties, the suggested NT3FS can also handle the input measurement errors. The rules of NT3FS are online tuned to better compensate the disturbances. By the input-output data set a data-driven scheme is designed, and a new LMI set is presented to ensure the stability. By several simulations and comparisons the superiority of the introduced control scheme is demonstrated.

Additive-multiplicative generator of logical connectives in fuzzy systems

2017 ◽  
Vol 2017 (45) ◽  
pp. 63-68
Author(s):  
R.A. Vorobel ◽  
Keyword(s):  
Fuzzy System ◽  
Fuzzy Systems ◽  
Functional Characteristics ◽  
Triangular Norms ◽  
Logical Operators ◽  
New Type ◽  
Logical Connectives ◽  
Basic Sets

The basic sets of logical connectives of fuzzy systems are analyzed. It is shown that triangular norms are the basis for constructing the operators for logical connectives. Two main classes are distinguished – conditional and algebraic. The known generators of operators of triangular norms are described. It is shown that they have limited functional characteristics. To expand them, a parameterized additive-multiplicative generator is proposed for constructing the logical operators of fuzzy systems. It is proved that this generator satisfies the requirements of the necessary axioms. Examples of construction of fuzzy system operators, which are generally known, are presented. The introduction of parameterized coefficient provides the obtaining of triangular norms of a new type.

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