A Creep Model of Steel Slag–Asphalt Mixture Based on Neural Networks
To characterize the complex creep behavior of steel slag–asphalt mixture influenced by both stress and temperature, predictive models employing Back Propagation (BP) and Long Short-Term Memory (LSTM) neural networks are described and compared in this paper. Multiple stress repeated creep recovery te...
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| Autori principali: | , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
MDPI AG
2024-07-01
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| Serie: | Applied Sciences |
| Soggetti: | |
| Accesso online: | https://www.mdpi.com/2076-3417/14/13/5820 |
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