弱奇异核模糊Volterra积分方程的分数阶谱伽辽金方法:正则性、收敛性和应用

IF 2.7 1区 数学 Q2 COMPUTER SCIENCE, THEORY & METHODS
Younes Talaei , Mahmoud A. Zaky , Ahmed S. Hendy
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引用次数: 0

摘要

具有弱奇异核的模糊Volterra积分方程具有在原点具有奇异行为的解。利用谱法求解标准(整阶)基函数的这类问题会产生低阶精度的近似解。本文讨论了利用分数阶基函数来提高谱伽辽金方法的精度。该方法的新矩阵形式将所考虑的问题转化为具有简单结构的代数方程组。数值实现表明该方法与其他方法相比是有效的。从理论上研究了该方法在加权l2范数下的收敛性分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A fractional spectral Galerkin method for fuzzy Volterra integral equations with weakly singular kernels: Regularity, convergence, and applications
Fuzzy Volterra integral equations with weakly singular kernels have solutions with singular behavior at the origin. Utilizing spectral methods on such problems with standard (integer-order) basis functions leads to generating approximate solutions with low-order accuracy. This paper deals with improving the accuracy of the spectral Galerkin method which can be applied to such problems by using fractional-order basis functions. New matrix formulation of the proposed method transforms the problem under consideration into a system of algebraic equations with a simple structure. Numerical implementation of the constructed method shows its effectiveness compared to other methods. The convergence analysis of the method is theoretically investigated in a weighted L2-norm.
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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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