Fuzzy graphs (FGs), broadly known as fuzzy incidence graphs (FIGs), have been recognized as being an effective tool to tackle real-world problems in which vague data and information are essential. Dominating sets (DSs) have multiple applications in diverse areas of life. In wireless networking, DSs are being used to find efficient routes with ad hoc mobile networks. In this paper, we extend the concept of domination of FGs to the FIGs and show some of their important properties. We propose the idea of order, size, and domination in FIGs. Two types of domination, namely, strong fuzzy incidence domination and weak fuzzy incidence domination, for FIGs are discussed. A relationship between strong fuzzy incidence domination and weak fuzzy incidence domination for complete fuzzy incidence graphs (CFIGs) is also introduced. An algorithm to find a fuzzy incidence dominating set (FIDS) and a fuzzy incidence domination number (FIDN) is discussed. Finally, an application of fuzzy incidence domination (FID) is provided to choose the best medical lab among different labs for the conduction of tests for the coronavirus.

中文翻译：

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算法的模糊关联图控制及在医学实验室选择中的应用

模糊图（FG），通常称为模糊关联图（FIG），已被认为是解决模糊数据和信息必不可少的现实问题的有效工具。支配集（DS）在生活的各个领域中都有多种应用。在无线网络中，DS被用于查找自组织移动网络的有效路由。在本文中，我们将控制FG的概念扩展到了图，并显示了它们的一些重要特性。我们在图1和图2中提出顺序，大小和支配的想法。讨论了两种类型的控制，即强模糊入射控制和弱模糊入射控制。还介绍了完整模糊入射图（CFIG）的强模糊入射支配和弱模糊入射支配之间的关系。讨论了一种寻找模糊关联度支配集（FIDS）和模糊关联度支配数（FIDN）的算法。最后，提供了一种应用模糊关联度控制（FID）的方法，可以在不同实验室中选择最佳的医学实验室进行冠状病毒检测。