Neural network and support vector machine models for the prediction of the liquefaction-induced uplift displacement of tunnels

Tunnels buried in liquefiable deposits are vulnerable to liquefaction-induced uplift damage during earthquakes. This paper presents support vector machine (SVM) and artificial neural network (ANN) models to predict the liquefaction-induced uplift displacement of tunnels based on artificial databases...

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Bibliografische Detailangaben
Hauptverfasser:	Gang Zheng, Wenbin Zhang, Wengang Zhang, Haizuo Zhou, Pengbo Yang
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	KeAi Communications Co., Ltd. 2021-04-01
Schriftenreihe:	Underground Space
Schlagworte:	Artificial neural network Support vector machine Liquefaction Uplift displacement
Online-Zugang:	http://www.sciencedirect.com/science/article/pii/S2467967419301011
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Neural network and support vector machine models for the prediction of the liquefaction-induced uplift displacement of tunnels

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