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Variational iterative method: an appropriate numerical scheme for solving system of linear Volterra fuzzy integro-differential equations

机译:变分迭代方法:求解线性波动模糊积分微分方程系统的适当数值方案

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摘要

Abstract In this research article, we focus on the system of linear Volterra fuzzy integro-differential equations and we propose a numerical scheme using the variational iteration method (VIM) to get a successive approximation under uncertainty aspects. We have 1 Uj(t)=f(t)+∫atk(t,x)u(x)dx, $$ {U}^{{j}} ( {t} ) ={f} ( {t} ) + int_{a}^{t} {k} ( {t},{x} ) {u} ( {x} ),dx, $$ where j refers to the jth order of the integro-differential equation and j=1,2,3,…,n $j=1, 2, 3,ldots,n$. k(t,x) $k(t, x)$ are integral kernel and a function of t andx, which arise in mathematical biology, physics and more. The variational iteration technique gives the more accurate results at the very small cost of iterations leading to exact solutions quickly. The benefits of the proposal, an algorithmic form of the VIM, are also designed. To illustrate the potentiality of the scheme, two test problems are given and the approximate solutions are compared with the exact solution and also represented graphically.
机译:摘要在本研究中,我们专注于线性Volterra模糊积分 - 微分方程的系统,我们提出了一种使用变分迭代方法(Vim)的数值方案,以在不确定方面获得连续近似。我们有1个UJ(t)= f(t)+∫atk(t,x)u(x)dx,$$ {u} ^ {{j}}({t})= {f}({t} )+ int_ {a} ^ {t} {k}({t},{x}){u}({x}),dx,$$,其中j指的是积分微分方程的第j个顺序j = 1,2,3,...,n $ j = 1,2,3, ldots,n $。 K(t,x)$ k(t,x)$是整体内核和t andx的函数,其在数学生物学,物理学和更多中出现。变分迭代技术以非常精确的迭代成本提供更准确的结果,从而快速地导致精确的解决方案。还设计了提案的好处,vim的算法形式。为了说明该方案的潜力,给出了两个测试问题,并将近似解决方案与精确的解决方案进行比较并且也以图形方式表示。

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