Numerical solution of fuzzy stochastic Volterra integral equations with constant delay

IF 3.2 1区 数学 Q2 COMPUTER SCIENCE, THEORY & METHODS
Xiaoxia Wen , Marek T. Malinowski , Hu Li , Hongyan Liu , Yan Li
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引用次数: 0

Abstract

This paper considers the nonlinear fuzzy stochastic Volterra integral equations with constant delay, which are general and include many fuzzy stochastic integral and differential equations discussed in literature. Since Doob's martingale inequality is no longer applicable to such equations, a new maximum inequality is obtained. Combining with the Picard approximation method, the existence and uniqueness of solutions to nonlinear fuzzy stochastic Volterra integral equations with constant delay are given. Moreover we prove that the solution behaves stably in the case of small changes of initial values, kernels and nonlinearities. We further develop a Euler-Maruyama (EM) scheme and prove the strong convergence of the scheme. It is shown that the strong convergence order of the EM method is 0.5 under Lipschitz condition. Moreover, the strong superconvergence order is 1 if further, the kernel h(t,s) of the stochastic term satisfies h(t,t)=0. Numerical examples demonstrated that the numerical results are consistent with the theoretical research conclusions. Furthermore, the application model of the fuzzy stochastic Volterra integral equation with constant delay in population dynamics is considered, and the exact solution of the numerical example is given in explicit form.

具有恒定延迟的模糊随机 Volterra 积分方程的数值解法
本文研究的是具有恒定延迟的非线性模糊随机 Volterra 积分方程,该方程具有普遍性,包括文献中讨论的许多模糊随机积分方程和微分方程。由于 Doob 的鞅不等式不再适用于这类方程,因此得到了一个新的最大不等式。结合 Picard 近似方法,我们给出了具有恒定延迟的非线性模糊随机 Volterra 积分方程的解的存在性和唯一性。此外,我们还证明了在初值、核和非线性微小变化的情况下,解的行为是稳定的。我们进一步开发了一种 Euler-Maruyama (EM) 方案,并证明了该方案的强收敛性。结果表明,在 Lipschitz 条件下,EM 方法的强收敛阶数为 0.5。此外,如果随机项的核满足 。数值实例表明,数值结果与理论研究结论一致。此外,还考虑了具有恒定延迟的模糊随机 Volterra 积分方程在种群动力学中的应用模型,并以显式给出了数值实例的精确解。
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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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