A hyper parameterized artificial neural network approach for prediction of the factor of safety against liquefaction

Soil liquefaction during earthquakes is a complex geotechnical engineering problem. Although various analytical approaches exist for predicting liquefaction risk, their limitations have led researchers to explore using artificial intelligence and machine learning methods. Machine learning has the po...

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Veröffentlicht in:	Engineering geology 2023-06, Vol.319, p.107109, Article 107109
Hauptverfasser:	Kurnaz, Talas Fikret, Erden, Caner, Kökçam, Abdullah Hulusi, Dağdeviren, Uğur, Demir, Alparslan Serhat
Format:	Artikel
Sprache:	eng
Schlagworte:	artificial intelligence Artificial neural networks Bayesian theory Factor of safety geology Hyperparameter optimization Machine learning model validation neural networks prediction regression analysis risk risk assessment Soil liquefaction
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