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AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
A [0, 1]-fuzzy $alpha$ -rank function on E is equivalent to a [0, 1]-fuzzy $beta$ -rank function on E.
📌 3 Key Takeaways
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Objective & Hypothesis:In this paper, the concepts of [0, 1]-fuzzy $beta$ -rank function and [0, 1]- fuzzy $alpha$ -rank function are presented.
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Key Findings & Data:The set of all closed and perfect [0, 1]-matroids (i.e. closed Goetschel-Voxman fuzzy matroids) on E and that of all [0, 1]-fuzzy $beta$ -rank functions on E are in one-to-one correspondence.
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Conclusion & Impact:A [0, 1]-fuzzy $alpha$ -rank function on E is equivalent to a [0, 1]-fuzzy $beta$ -rank function on E.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters
Abstract
In this paper, the concepts of [0, 1]-fuzzy $beta$ -rank function and [0, 1]- fuzzy $alpha$ -rank function are presented. The set of all closed and perfect [0, 1]-matroids (i.e. closed Goetschel-Voxman fuzzy matroids) on E and that of all [0, 1]-fuzzy $beta$ -rank functions on E are in one-to-one correspondence. A [0, 1]-fuzzy $alpha$ -rank function on E is equivalent to a [0, 1]-fuzzy $beta$ -rank function on E.
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Cite This Article
XIN, X., LIAN, H. (2022). [0,1]-Fuzzy $beta$-rank functions. Hacettepe Journal of Mathematics and Statistics, Cilt: 41 - Sayı: 1, 59–65. https://ajindex.com/articles/530497