Combinations of lattice-valued coarse structures and groups

IF 3.2 1区 数学 Q2 COMPUTER SCIENCE, THEORY & METHODS
Yongchao Wang , Bin Pang , Fu-Gui Shi
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引用次数: 0

Abstract

Based on a complete residuated lattice L, we combine the lattice-valued coarse structures and group operations to propose the concept of L-fuzzifying coarse groups. Then we introduce the notion of L-fuzzifying group ideals and establish its one-to-one correspondence with L-fuzzifying coarse groups. Specifically, we examine how L-fuzzifying coarse structures align with the algebraic structures of the supporting group. Finally, we use L-fuzzifying group ideals to characterize a fuzzy coarse equivalence between L-fuzzifying coarse groups, presenting some results derived from the kernel of the group homomorphism.
基于完整残差网格 L,我们将网格值粗结构和群运算结合起来,提出了 L-模糊粗群的概念。然后,我们引入了 L-模糊化群理想的概念,并建立了它与 L-模糊化粗群的一一对应关系。具体来说,我们研究了 L-模糊化粗群结构如何与支持群的代数结构相一致。最后,我们利用 L-模糊化群理想来表征 L-模糊化粗糙群之间的模糊粗糙等价性,并提出了从群同态的内核得出的一些结果。
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来源期刊
Fuzzy Sets and Systems
Fuzzy Sets and Systems 数学-计算机:理论方法
CiteScore
6.50
自引率
17.90%
发文量
321
审稿时长
6.1 months
期刊介绍: Since its launching in 1978, the journal Fuzzy Sets and Systems has been devoted to the international advancement of the theory and application of fuzzy sets and systems. The theory of fuzzy sets now encompasses a well organized corpus of basic notions including (and not restricted to) aggregation operations, a generalized theory of relations, specific measures of information content, a calculus of fuzzy numbers. Fuzzy sets are also the cornerstone of a non-additive uncertainty theory, namely possibility theory, and of a versatile tool for both linguistic and numerical modeling: fuzzy rule-based systems. Numerous works now combine fuzzy concepts with other scientific disciplines as well as modern technologies. In mathematics fuzzy sets have triggered new research topics in connection with category theory, topology, algebra, analysis. Fuzzy sets are also part of a recent trend in the study of generalized measures and integrals, and are combined with statistical methods. Furthermore, fuzzy sets have strong logical underpinnings in the tradition of many-valued logics.
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