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On the numerical solution of fractional stochastic integro-differential equations via meshless discrete collocation method based on radial basis functions

机译:基于径向基函数的无网状离散搭配方法在分数随机积分 - 微分方程的数值解

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The main intention of the present work is to develop a numerical scheme based on radial basis functions (RBFs) to solve fractional stochastic integro-differential equations. In this paper, the solution of fractional stochastic integro-differential equation is approximated by using strictly positive definite RBFs such as Gaussian and strictly conditionally positive definite RBFs such as thin plate spline. Then, the quadrature methods are used to approximate the integrals which are appeared in this scheme. When we use thin plate spline to approximate the solution of mentioned equation, we encounter logarithm-like singular integrals which cannot be computed by common quadrature formula. To overcome this difficulty, we introduce the non-uniform composite Gauss-Legendre integration rule and employ it to estimate the singular logarithm integral appeared in this case. This method transforms the solution of linear fractional stochastic integro-differential equations to the solution of linear system of algebraic equations which can be easily solved. We also discuss the error analysis of the proposed method and demonstrate that the rate of convergence of this approach is arbitrary high for infinitely smooth RBFs. Finally, the efficiency and accuracy of the proposed method are checked by some numerical examples.
机译:本作工作的主要目的是基于径向基函数(RBF)来开发数值方案,以解决分数随机积分微分方程。在本文中,通过使用严格的正定RBF,例如高斯和严格条件为正定的RBF,例如薄板样条,分数随机积分 - 微分方程的溶解近似。然后,正交方法用于近似于在该方案中出现的积分。当我们使用薄板样条近似提到等式的解决方案时,我们遇到了不能通过常见的正交公式计算的对数样奇异积分。为了克服这种困难,我们介绍了非统一的复合高斯 - Legendre集成规则,并采用它来估计这种情况下出现的奇异对数积分。该方法将线性分数随机积分 - 微分方程的解决方案转换为可以容易解决的代数方程的线性系统的解。我们还讨论了所提出的方法的误差分析,并证明这种方法的收敛速度是无限光滑的RBF的任意高。最后,通过一些数值示例检查所提出的方法的效率和准确性。

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