Research on prediction of nanocrystalline alloy hysteresis properties based on long short-term memory network
Abstract In order to predict the hysteresis characteristics of nanocrystalline alloy materials at different frequencies, a data-driven hysteresis prediction model based on the encoder–decoder architecture, which combines long short-term memory network and feedforward neural network, is proposed in t...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-02-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-91138-1 |
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