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A novel approach for analyzing the behavior of industrial systems using weakest t-norm and intuitionistic fuzzy set theory

机译:基于最弱t范数和直觉模糊集理论的工业系统行为分析新方法

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摘要

The present work investigates the various reliability parameters of industrial systems in terms of membership and non-membership functions by using α-cut and the weakest t-norm based arithmetic operations on triangular intuitionistic fuzzy sets. As the available information about the constituent components of the system is most of the time imprecise, incomplete, vague and conflicting, the management decisions are based on experience. Thus, the objective of this paper is to quantify the uncertainties that make the decisions realistic, generic and extensible for the application domain. Sensitivity of system performance has also been analyzed for showing the effect of taking wrong combinations of reliability parameters. The obtained results computed by the proposed approach are compared with the existing methodologies. The approach has been illustrated through a case study for supremacy.
机译:本文通过在三角形直觉模糊集上使用α割和基于最弱t范数的算术运算,研究了隶属函数和非隶属函数方面的工业系统的各种可靠性参数。由于有关系统组成部分的可用信息大多数时候都不准确,不完整,含糊和冲突,因此管理决策是基于经验的。因此,本文的目的是量化不确定性,这些不确定性使决策对于应用程序领域来说是现实的,通用的和可扩展的。还分析了系统性能的敏感性,以显示错误地组合可靠性参数的影响。将所提出的方法计算出的结果与现有方法进行比较。通过至高无上的案例研究说明了该方法。

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