计算哥德尔结构上模糊极小极大网络的标记

中文摘要 AI 辅助

模糊极小极大网络是用于计算两个基于有限模糊图的结构之间最大模糊双模拟和模拟的工具。本文为计算哥德尔结构上有限模糊极小极大网络的最大正确标记提供了一种高效算法，其时间复杂度与输入网络中的节点数和正边数呈线性关系。在此基础上，我们推导出了第一个用于计算哥德尔结构上两个有限模糊图之间最大模糊有向模拟的算法，时间复杂度为\(O((m + n)n)\)，其中\(n\)和\(m\)分别表示输入图中的顶点总数和正边总数。

英文摘要

Fuzzy minimax nets were recently introduced as a tool for computing the greatest fuzzy bisimulation and simulation between two finite fuzzy graph-based structures. In this work, we provide an efficient algorithm with time complexity $O(m + n + l\log{l})$ for computing the greatest correct marking of a finite fuzzy minimax net over the Gödel structure, where $n$, $m$, and $l$ denote the numbers of nodes, positive edges, and distinct fuzzy values used in the net, respectively. Building on this result, we derive the first algorithm with time complexity $O((m+n)n)$ for computing the greatest fuzzy directed simulation between two finite fuzzy graphs over the Gödel structure, where $n$ and $m$ denote the total numbers of vertices and positive edges, respectively, in the input graphs.

发表机构

• Institute of Informatics, University of Warsaw（华沙大学信息学研究所）
• Faculty of Information Technology, Nguyen Tat Thanh University（胡志明市阮梯青大学信息技术学院）

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