PhyCRNet: physics-informed convolutional-recurrent network for solving spatiotemporal PDEs (Q2072500)

scientific article; zbMATH DE number 7464518

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English	PhyCRNet: physics-informed convolutional-recurrent network for solving spatiotemporal PDEs	scientific article; zbMATH DE number 7464518

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instance of

scholarly article

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title

PhyCRNet: physics-informed convolutional-recurrent network for solving spatiotemporal PDEs (English)

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author

Yanyan Li

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published in

Computer Methods in Applied Mechanics and Engineering

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publication date

26 January 2022

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full work available at URL

https://arxiv.org/abs/2106.14103

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zbMATH Keywords

convolutional-recurrent learning

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partial differential equations

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encoder-decoder

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physics-informed deep learning

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residual connection

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hard-encoding of I/BCs

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On the limited memory BFGS method for large scale optimization

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describes a project that uses

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Identifiers

Mathematics Subject Classification ID

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10.1016/J.CMA.2021.114399

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Sitelinks

Mathematics(1 entry)

mardi Publication:2072500