On fuzzy fractions formation

IF 2.7 1区 数学 Q2 COMPUTER SCIENCE, THEORY & METHODS
Naser Zamani , Zeinab Rezaei
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引用次数: 0

Abstract

Let R be a commutative ring, S a multiplicatively closed subset of R and let S1R be the ring of fractions over S. For a typical fuzzy submodule η of the R-module M, the fuzzy fractions S1η of μ is a fuzzy submodule of the S1R-module (of fractions) S1M. In this note, it is shown that if μλ are two fuzzy submodules of M, both having sup property, then there exist a (fuzzy sense) isomorphism between S1(λ/μ) and S1λ/S1μ. Then, it is seen that local global principle holds true for fuzzy submodules. Furthermore, after providing some auxiliary results, it is proved that under some mild conditions, fuzzy fractions formation commutes with fuzzy residual quotient.
关于模糊分数的形成
设R是一个交换环,S是R的乘法闭子集,S - 1R是S上的分数环。对于R模M的一个典型模糊子模η, μ的模糊分数S - 1η是S - 1R(分数)模S - 1M的模糊子模。本文证明,如果μ≥λ是M的两个模糊子模,且均具有sup性质,则S−1(λ/μ)与S−1λ/S−1μ之间存在(模糊意义上的)同构。然后,可以看出局部全局原理对模糊子模块是成立的。进一步,在给出一些辅助结果后,证明了在一些温和的条件下,模糊分数的形成与模糊残商的形成是一致的。
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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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