Like bisimulations, simulations and directed simulations are used for analyzing graph-based structures such as automata, labeled transition systems, linked data networks, Kripke models and interpretations in description logic. Simulations characterize the class of existential modal formulas, whereas directed simulations characterize the class of positive modal formulas. These notions are worth studying. For example, one may be interested in checking whether a given finite automaton simulates another or whether an object in a linked data network has all positive properties that another object has. To deal with vagueness and uncertainty, fuzzy graph-based structures are used instead of crisp ones. In this article, we design efficient algorithms with the complexity $O((m+n)n)$ for computing the largest crisp simulation and the largest crisp directed simulation between two finite fuzzy labeled graphs, where $n$ is the number of vertices and $m$ is the number of nonzero edges of the input fuzzy graphs. We also adapt them to computing the largest crisp simulation and the largest crisp directed simulation between two finite fuzzy automata.
翻译:类似模拟、 模拟和直接模拟用于分析基于图形的结构, 如自动成像、 标签的过渡系统、 链接的数据网络、 Kripke 模型和描述逻辑解释等。 模拟是存在模式公式的特征, 而定向模拟是正式公式的特征。 这些概念值得研究。 例如, 人们可能有兴趣检查一个特定限量的自动成像是否模拟另一个, 或者链接的数据网络中的某个对象是否具有另一个对象的全部正性。 为了处理模糊性和不确定性, 使用模糊性图形结构, 而不是直线结构。 在本篇文章中, 我们设计了使用最复杂( $O (m+n)n) 的高效算法, 用于计算最大的正式模拟, 而最大的直线模拟是两个最小的模糊标签图形之间的最大直线模拟。 其中, $是脊椎数, $ 和 $m 美元是输入的烟雾图形的非零边缘数。 我们还调整了它们来计算最大的正式模拟, 和两个硬式自动成形之间的最大直径模拟。