A deep domain decomposition method based on Fourier features
نویسندگان
چکیده
In this paper we present a Fourier feature based deep domain decomposition method (F-D3M) for partial differential equations (PDEs). Currently, neural network methods are actively developed solving PDEs, but their efficiency can degenerate problems with high frequency modes. new F-D3M strategy, overlapping is conducted the spatial domain, such that modes be reduced to relatively low ones. each local subdomain, multi networks (MFFNets) constructed, where efficient boundary and interface treatments applied corresponding loss functions. We general mathematical framework of F-D3M, validate its accuracy demonstrate numerical experiments.
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ژورنال
عنوان ژورنال: Journal of Computational and Applied Mathematics
سال: 2023
ISSN: ['0377-0427', '1879-1778', '0771-050X']
DOI: https://doi.org/10.1016/j.cam.2022.114963