In this paper, we study the numerical method for solving forward-backward stochastic differential equations driven by G-Brownian motion (G-FBSDEs) which correspond to fully nonlinear partial differential equations (PDEs). First, we give an approximate conditional G-expectation and obtain some feasible methods to calculate the distribution of G-Brownian motion. On this basis, some efficient numerical schemes for G-FBSDEs are then proposed. We rigorously analyze the errors of the proposed schemes and prove the convergence. Finally, several numerical experiments are presented to demonstrate the accuracy of our schemes.

中文翻译：

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由G-布朗运动驱动的向前-向后随机微分方程的一种高效数值方法。

在本文中，我们研究了求解由G-布朗运动（G -FBSDEs）驱动的正向-后向随机微分方程的数值方法，该方法对应于完全非线性的偏微分方程（PDE）。首先，我们给出了近似的条件G-期望值，并获得了一些可行的方法来计算G-布朗运动的分布。在此基础上，提出了一些有效的G -FBSDE数值方案。我们严格分析了所提方案的误差，证明了收敛性。最后，提出了几个数值实验，以证明我们的方案的准确性。