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An Approach for Analyzing Fuzzy System Reliability Using Particle Swarm Optimization and Intuitionistic Fuzzy Set Theory

机译:基于粒子群和直觉模糊集理论的模糊系统可靠性分析方法。

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The main objective of the paper is to present a hybridized technique named as particle swarm optimization based vague cut set (PSOBVCS) for determining the membership and non-membership function of fuzzy system reliability. In the literature so far on the vague set, system reliability is evaluated using a fuzzy arithmetic operation on the collected imprecise, vague or uncertain data. This may contain the wide spread of the reliability and hence cannot give a right decision to decision makers. So in order to remove the uncertainty up to the desired degree, an attempt has been made in this paper in which an expression of system reliability is evaluated using ordinary arithmetic operations instead of fuzzy arithmetic operation and particle swarm optimization has been used to construct their membership functions. The effectiveness of the proposed approach is illustrated with analyze of the fuzzy reliability of scries, parallel and series-parallel systems using different types of intuitionistic fuzzy failure rates. The computed results from the analysis have a less range of uncertainty as the comparability of existing results.
机译:本文的主要目的是提出一种基于粒子群优化的模糊割集(PSOBVCS)的混合技术,用于确定模糊系统可靠性的隶属度和非隶属度函数。迄今为止,在有关模糊集的文献中,对收集的不精确,模糊或不确定的数据使用模糊算术运算来评估系统可靠性。这可能包含可靠性的广泛传播,因此不能为决策者提供正确的决策。因此,为了消除不确定性达到期望的程度,本文尝试使用普通算术运算而不是模糊算术运算来评估系统可靠性的表达式,并使用粒子群算法来构造其隶属度。功能。通过使用不同类型的直觉模糊故障率分析串联,并联和串并联系统的模糊可靠性,说明了该方法的有效性。分析的计算结果与现有结果的可比性相比,具有较小的不确定性范围。

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