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Moving least square - one dimensional integrated radial basis function networks for time dependent problems

机译:移动最小二乘 - 一维集成径向基函数网络,用于时间依赖性问题

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This paper presents a new numerical procedure for time-dependent problems. The partition of unity method is employed to incorporate the moving least square and one-dimensional integrated radial basis function networks (MLS-1D-IRBFN) techniques in an approach that produces a very sparse system matrix and offers as a high order of accuracy as that of global 1D-IRBFN method. Moreover, the proposed approach possesses the Kronecker-δ property which helps impose the essential boundary condition in an exact manner. Spatial derivatives are discretised using Cartesian grids and MLS-1D-IRBFN, whereas temporal derivatives are discretised using high-order time-stepping schemes, namely standard θ and fourth-order Runge-Kutta methods. Several numerical examples including two-dimensional diffusion equation, one-dimensional advection-diffusion equation and forced vibration of a beam are considered. Numerical results show that the current methods are highly accurate and efficient in comparison with other published results available in the literature.
机译:本文提出了一种新的数值依赖性问题的数值过程。使用统一方法的分区来纳入移动最小二乘和一维综合径向基函数网络(MLS-1D-IRBFN)技术,以产生非常稀疏的系统矩阵,提供高阶的准确性全局1D-IRBFN方法。此外,所提出的方法具有Kronecker-Δ的性质,其有助于以确切的方式施加必要的边界条件。使用笛卡尔栅格和MLS-1D-IRBFN离散空间衍生物,而使用高阶时间步进方案,即标准θ和四阶runge-kutta方法离散地区衍生物。考虑了几个数值示例,包括二维扩散方程,一维平行扩散方程和光束的强制振动。数值结果表明,与文献中可用的其他公开的结果相比,目前的方法是高度准确和高效的。

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