给定下界正集的闭区间正集的关联运算

IF 8.1 1区 计算机科学 0 COMPUTER SCIENCE, INFORMATION SYSTEMS
Yexing Dan, Xiaodong Pan
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引用次数: 0

摘要

在包含令下,我们的重点是探索给定下界正集的闭区间正集上的关联二元运算。起初,我们提出了一种方法,将给定下界正集上的递增关联二元运算扩展到给定下界正集的封闭区间正集。这涉及在给定的下界正集和它的一个子集之间使用一个内部算子,同时在同一下界正集上使用另一个适当选择的递增和关联二元运算。随后,我们将探讨在哪些条件下,这种扩展运算可以促进给定有界正集的闭区间正集上的 t 准则和 t 准则的构造。最后,我们深入探讨所构造的 t-conorms 和 t-norms 的性质,特别是阿基米德性质以及幂等元素和零等元素的存在。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Associative operations on the poset of closed intervals of a given lower-bounded poset
Under the inclusion order, our focus lies in exploring associative binary operations on the poset of closed intervals of a given lower-bounded poset. Initially, we propose a method for extending an increasing and associative binary operation on a given lower-bounded poset to the poset of closed intervals of that given lower-bounded poset. It involves the use of an interior operator between that given lower-bounded poset and one of its subposets, alongside another appropriately chosen increasing and associative binary operation on the same lower-bounded poset. Subsequently, we explore conditions under which this extended operation can facilitate the constructions of t-conorms and t-norms on the poset of closed intervals of a given bounded poset. Lastly, we delve into the properties of the constructed t-conorms and t-norms, specifically addressing the Archimedean property and the existence of idempotent and nilpotent elements.
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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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