Optimal AI Model for Accurate Classification of Squeezing in Underground Structures

Assessing ground conditions with regard to the potential for squeezing and the behavior of geological structures is a crucial aspect of designing underground structures. Tunnel construction in conditions where squeezing occurs can be a challenging and time-consuming process. Recognizing and evaluati...

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Veröffentlicht in:	Geotechnical and geological engineering Jg. 43; H. 2; S. 65
Hauptverfasser:	Fattahi, Hadi, Mohtarami, Ehsan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Cham Springer International Publishing 01.02.2025 Springer Nature B.V
Schlagworte:	Artificial intelligence Civil Engineering Classification Compressing Construction Decision trees Earth and Environmental Science Earth Sciences Evaluation Excavation Geological structures Geotechnical Engineering & Applied Earth Sciences Hydrogeology Neural networks Original Paper Risk reduction Support systems Support vector machines Terrestrial Pollution Tunnel construction Tunnels Underground construction Underground structures Waste Management/Waste Technology Weak rock Underground structures Squeezing phenomenon Classification models Artificial intelligence
ISSN:	0960-3182, 1573-1529
Online-Zugang:	Volltext
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