Various networks such as cloud computing, water/gas/electricity networks, wireless sensor networks, transportation networks, and 4G/5G networks, have become an integral part of our daily lives. A binary-state network (BN) is often used to model network structures and applications. The BN reliability is the probability that a BN functions continuously; that is, that there is always a simple path connected between a specific pair of nodes. This metric is a popular index for designing, managing, controlling, and evaluating networks. The traditional BN reliability assumes that the reliability of each arc is known in advance. However, this is not always the case. Functioning components operate under different environments; moreover, a network might have newly installed components. Hence, the reliability of these components is not always known. To resolve the aforementioned problems, in which the reliability of some components of a network are uncertain, we introduce the fuzzy concept for the analysis of these components, and propose a new algorithm to solve this uncertainty-component BN reliability problem. The time complexity of the proposed algorithm is analyzed, and the superior performance of the algorithm is demonstrated through examples.

中文翻译：

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使用不确定性分量计算节点上的活动二元状态可靠性

云计算、水/气/电网络、无线传感器网络、交通网络和4G/5G网络等各种网络已成为我们日常生活中不可或缺的一部分。二元状态网络 (BN) 通常用于对网络结构和应用程序进行建模。BN的可靠性是BN连续运行的概率；也就是说，在特定的一对节点之间总是有一条简单的路径连接。该指标是用于设计、管理、控制和评估网络的流行指标。传统的BN可靠性假设每个弧的可靠性是预先知道的。然而，这并非总是如此。功能组件在不同环境下运行；此外，网络可能有新安装的组件。因此，这些组件的可靠性并不总是已知的。为了解决上述问题，其中网络的某些组件的可靠性是不确定的，我们引入了对这些组件的分析的模糊概念，并提出了一种新的算法来解决这个不确定性组件 BN 可靠性问题。分析了所提算法的时间复杂度，并通过实例展示了该算法的优越性能。