通过最大独立元素求模糊关系方程的最小解

IF 8.1 1区 计算机科学 0 COMPUTER SCIENCE, INFORMATION SYSTEMS
David Lobo , Jesús Medina , Timo Camillo Merkl , Reinhard Pichler
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引用次数: 0

摘要

模糊关系方程(FRE)是一种有用的形式主义,在不同的计算机科学领域有着广泛的应用。测试是否存在解,以及如果存在,计算唯一的最大解都很简单。相比之下,最小解的计算则更为复杂。特别是,即使在结构非常简单的 FRE 中,极小解的数量也会呈指数级增长。然而,极小解非常有用,因为在温和的条件下,极小解(连同最大解)可以让我们描述 FRE 的整个解空间。这项研究的主要成果是一种枚举最小解集合的新方法。它通过建立 FRE 的覆盖和(超)盒的最大独立元素之间的关系来实现。因此,我们可以使(超)盒的最大独立元素的高效枚举方法也适用于我们的 FRE 设置,在 FRE 设置中,模糊关系组成中考虑的算子只需要保留任意子集的上界和非空子集的下界。更具体地说,我们因此证明,枚举 FRE 的最小解可以用增量准多项式延迟来完成。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Minimal solutions of fuzzy relation equations via maximal independent elements
Fuzzy relation equations (FRE) are a useful formalism with a broad number of applications in different computer science areas. Testing if a solution exists and, if so, computing the unique greatest solution is straightforward. In contrast, the computation of minimal solutions is more complex. In particular, even in FRE with a very simple structure, the number of minimal solutions can increase exponentially. However, minimal solutions are immensely useful since, under mild conditions, they (together with the greatest solution) allow one to describe the entire space of solutions to an FRE. The main result of this work is a new method for enumerating the set of minimal solutions. It works by establishing a relationship between coverings of FRE and maximal independent elements of (hyper-)boxes. We can thus make efficient enumeration methods for maximal independent elements of (hyper-)boxes applicable also to our setting of FRE, where the operator considered in the composition of fuzzy relations only needs to preserve suprema of arbitrary subsets and infima of non-empty subsets. More specifically, we thus show that the enumeration of the minimal solutions of an FRE can be done with incremental quasi-polynomial delay.
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来源期刊
Information Sciences
Information Sciences 工程技术-计算机:信息系统
CiteScore
14.00
自引率
17.30%
发文量
1322
审稿时长
10.4 months
期刊介绍: Informatics and Computer Science Intelligent Systems Applications is an esteemed international journal that focuses on publishing original and creative research findings in the field of information sciences. We also feature a limited number of timely tutorial and surveying contributions. Our journal aims to cater to a diverse audience, including researchers, developers, managers, strategic planners, graduate students, and anyone interested in staying up-to-date with cutting-edge research in information science, knowledge engineering, and intelligent systems. While readers are expected to share a common interest in information science, they come from varying backgrounds such as engineering, mathematics, statistics, physics, computer science, cell biology, molecular biology, management science, cognitive science, neurobiology, behavioral sciences, and biochemistry.
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