Three Algorithms for Solving High-Dimensional Fully Coupled FBSDEs Through Deep Learning
Three Algorithms for Solving High-Dimensional Fully Coupled FBSDEs Through Deep Learning
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DOI：
10.1109/mis.2020.2971597
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发表时间：
2019-07
影响因子：
6.4
通讯作者：
Shaolin Ji;S. Peng;Ying Peng;Xichuan Zhang
中科院分区：
文献类型：
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作者：
Shaolin Ji;S. Peng;Ying Peng;Xichuan Zhang
近年来，深度学习方法因其对高维问题具有良好的精度和性能，已被用于求解正倒向随机微分方程和抛物型偏微分方程。在本文中，我们主要通过深度学习求解全耦合FBSDEs，并提供了三种算法，数值结果显示了显著的性能，特别是在高维情况下。
Recently, the deep learning method has been used for solving forward–backward stochastic differential equations (FBSDEs) and parabolic partial differential equations, as it has good accuracy and performance for high-dimensional problems. In this article, we mainly solve fully coupled FBSDEs through deep learning and provide three algorithms, and the numerical results show remarkable performance, especially for high-dimensional cases.