English(EN) Hybrid coupling with numerics-informed neural networks and the overlapping Schwarz alternating method

新的混合框架将神经网络与经典模型耦合

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-17 04:00

研究人员开发了一个混合建模框架，该框架结合了预训练的数值信息神经网络（NINNs）和使用重叠施瓦茨交替法的经典全阶模型（FOMs）。该方法在二维对流-扩散方程的对流主导区域进行了测试。研究表明，与传统的物理信息神经网络（PINNs）不同，单片NINN可以在没有域分解的情况下进行精确训练。该混合框架将预训练的NINN与相邻的FOM耦合，在施瓦茨迭代期间保持NINN权重固定，并通过自顶向下和自底向上两种训练策略实现了与全FOM-FOM施瓦茨解相当的精度。 AI

影响这项研究通过结合神经网络和传统数值方法的优势，有望实现更高效、更精确的模拟。

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在 arXiv cs.LG 阅读 →

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报道来源 [1]

arXiv cs.LG TIER_1 English(EN) · George Chumbipuma, Irina Tezaur, Alejandro Diaz, Beatrice Riviere · 2026-09-17 04:00

数值驱动神经网络与重叠施瓦茨交替法的混合耦合

arXiv:2609.17841v1 Announce Type: new Abstract: We develop a hybrid modeling framework for coupling pre-trained numerics-informed neural networks (NINNs) with classical full order models (FOMs) using the overlapping Schwarz alternating method. We consider the two-dimensional adve…

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数值驱动神经网络与重叠施瓦茨交替法的混合耦合

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