基于新阈值策略的二维椭圆方程增强自适应RBF-FD方法

IF 0.3 Q4 MATHEMATICS
Oanh Thi Dang
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引用次数: 0

摘要

在本文中,我们提出了在每个细化步骤中确定误差指示器阈值的策略。误差指标阈值不直接从最大误差指标中计算,提高了细化效率。此外,为了提高改进效率,我们提出了三种新的候选中心结构,它们包含更多的中心,并且可能使分布密度增加一倍。此外,我们改进了可变支持大小算法,使其更加灵活。此外,我们还引入了一种衡量自适应RBF-FD(径向基函数-有限差分)无网格法生成的每个新中心的平均递归预处理成本的方法。该指标用于评估自适应RBF-FD无网格方法的预处理成本效率,并将其与我们之前发表的求解二维椭圆方程的自适应RBF-FD方法进行比较。结果表明,与以往的研究和自适应有限元法相比,本文方法得到的数值解在计算成本最低的情况下,精度更高,稳定性更强,精细化效果更好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhanced Adaptive RBF-FD Methods for 2D Elliptic Equations with New Thresholding Strategies

In this paper, we present strategies for determining the error indicator threshold value at each refinement step. The error indicator threshold is not directly computed from the maximum error indicator, improving refinement efficiency. Moreover, to enhance refinement efficiency, we propose three new candidate center structures, which include a greater number of centers and may double the distribution density. Additionally, we improve the variable support size algorithm for making it more flexible. Moreover, we introduce a measure to evaluate the average recursive preprocessing cost per new center generated by the adaptive RBF-FD (Radial Basis Function-Finite Difference) meshless method. This metric is used to assess the preprocessing cost efficiency of the adaptive RBF-FD meshless method and to compare it with our previously published adaptive RBF-FD methods for solving 2D elliptic equations. The results demonstrate that the numerical solutions obtained using the methods proposed in this paper are significantly more accurate, more stable, and more effective in terms of refinement than those from our earlier studies and the adaptive FEM (Finite Element Method), while achieving the lowest computational cost.

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来源期刊
CiteScore
0.90
自引率
0.00%
发文量
23
期刊介绍: Acta Mathematica Vietnamica is a peer-reviewed mathematical journal. The journal publishes original papers of high quality in all branches of Mathematics with strong focus on Algebraic Geometry and Commutative Algebra, Algebraic Topology, Complex Analysis, Dynamical Systems, Optimization and Partial Differential Equations.
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