Výsledky vyhledávání - "Lin, Guochang"

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NSNO: Neumann Series Neural Operator for Solving Helmholtz Equations in Inhomogeneous Medium

Autor: Chen, Fukai, Liu, Ziyang, Lin, Guochang, Chen, Junqing, Shi, Zuoqiang

In this paper, we propose Neumann Series Neural Operator (NSNO) to learn the solution operator of Helmholtz equation from inhomogeneity coefficients and source terms to solutions. Helmholtz equation is a crucial partial differential equation (PDE) wi

Externí odkaz: http://arxiv.org/abs/2401.13494

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BI-GreenNet: Learning Green's functions by boundary integral network

Autor: Lin, Guochang, Chen, Fukai, Hu, Pipi, Chen, Xiang, Chen, Junqing, Wang, Jun, Shi, Zuoqiang

Green's function plays a significant role in both theoretical analysis and numerical computing of partial differential equations (PDEs). However, in most cases, Green's function is difficult to compute. The troubles arise in the following three folds

Externí odkaz: http://arxiv.org/abs/2204.13247

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Akademický článek

High-performance artificial SEI layer with high elastic modulus and multiple Li-ion channels

Autor: Zheng, Chao, Lin, Guochang, Tan, Huifeng, Zhang, Yaohui, Lv, Zhe

Publikováno v: In Journal of Energy Storage 20 December 2024 104 Part B

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BINet: Learning to Solve Partial Differential Equations with Boundary Integral Networks

Autor: Lin, Guochang, Hu, Pipi, Chen, Fukai, Chen, Xiang, Chen, Junqing, Wang, Jun, Shi, Zuoqiang

We propose a method combining boundary integral equations and neural networks (BINet) to solve partial differential equations (PDEs) in both bounded and unbounded domains. Unlike existing solutions that directly operate over original PDEs, BINet lear

Externí odkaz: http://arxiv.org/abs/2110.00352

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