Improving the Accuracy of Jiles-Atherton Hysteresis Loop Cluster Simulations in Low Saturation Regions with Neural Networks
Author:
Affiliation:
1. State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, China
2. Honghe Power Supply Bureau of Yunnan Power Grid, Honghe Power Supply Bureau of Yunnan Power Grid, China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3608251.3608268
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4. Neural Network Modeling of Arbitrary Hysteresis Processes: Application to GO Ferromagnetic Steel
5. Deep neural networks for the efficient simulation of macro-scale hysteresis processes with generic excitation waveforms
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