Magnetic Field Analysis of Reactor Based on TL-PIDL and Time Domain PIDL
Author:
Affiliation:
1. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Baoding, China
Funder
S&T Program of Hebei
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx8/77/10525238/10633846.pdf?arnumber=10633846
Reference7 articles.
1. Comparison of Parallel-in-Space-and-Time Finite-Element Methods for Magnetic Field Analysis of Electric Machines
2. Rigorous a Posteriori Error Bounds for PDE-Defined PINNs
3. A High-Efficient Hybrid Physics-Informed Neural Networks Based on Convolutional Neural Network
4. Physics-Informed Neural Networks for Solving 2-D Magnetostatic Fields
5. Structured Neural Decoding With Multitask Transfer Learning of Deep Neural Network Representations
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