模糊函数广义微分性的表征结果

IF 3.2 1区数学 Q2 COMPUTER SCIENCE, THEORY & METHODS

Fuzzy Sets and Systems Pub Date : 2024-06-07 DOI:10.1016/j.fss.2024.109038

Felipe Longo , Beatriz Laiate , Marta C. Gadotti , João F. da C.A. Meyer

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引用次数: 0

摘要

本文介绍了模糊函数和区间值函数的所谓广义导数的新性质，这些导数包括这些函数的 gH、gH⁎ 和 g-导数。有关区间值函数广义导数的几个最新性质被扩展到模糊情况，并为其提供了一般表征结果。最后，为了说明所提出的结果，研究了考虑到模糊人口的马尔萨斯增长和衰减模型。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Characterization results of generalized differentiabilities of fuzzy functions

This paper presents new properties of the so-called generalized derivatives of fuzzy and interval-valued functions, which consist of the gH, gH⁎, and g-derivatives of these functions. Several recent properties concerning the generalized derivatives of interval-valued functions are extended to the fuzzy case, for which general characterization results are provided. Lastly, in order to illustrate the presented results, a study on the Malthusian growth and decay models considering fuzzy populations is made.

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来源期刊

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.