Further investigation of convolutional neural networks applied in computational electromagnetism under physics‐informed consideration

Abstract Convolutional neural networks (CNN) have shown great potentials and have been proven to be an effective tool for some image‐based deep learning tasks in the field of computational electromagnetism (CEM). In this work, an energy‐based physics‐informed neural network (EPINN) is proposed for l...

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Bibliografische Detailangaben

Hauptverfasser:	Ruohan Gong, Zuqi Tang
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	Wiley 2022-06-01
Schriftenreihe:	IET Electric Power Applications
Schlagworte:	computational electromagnetics finite element analysis learning (artificial intelligence) numerical analysis
Online-Zugang:	https://doi.org/10.1049/elp2.12183
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