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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Hlavní autoři:	Bei Deng, Guowei Zeng, Rui Ge
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	MDPI AG 2024-07-01
Edice:	Applied Sciences
Témata:	steel slag–asphalt mixture creep recovery testing BP neural network LSTM neural network creep model k-fold cross-validation
On-line přístup:	https://www.mdpi.com/2076-3417/14/13/5820
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