A comparative study of different machine learning algorithms in predicting EPB shield behaviour: a case study at the Xi’an metro, China

Complex geological conditions and/or inappropriate shield tunnel boring machine (TBM) operation can significantly degrade both the excavation and safety of tunnel construction. In recent years, the excavation behaviour of shield TBMs has been a popular topic in the literature given the large volume...

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Vydané v:	Acta geotechnica Ročník 16; číslo 12; s. 4061 - 4080
Hlavní autori:	Bai, Xue-Dong, Cheng, Wen-Chieh, Li, Ge
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2021 Springer Nature B.V
Predmet:	Accuracy Algorithms Boring machines Comparative analysis Comparative studies Complex Fluids and Microfluidics Data analysis Decision trees Drilling & boring machinery Earth pressure Engineering Excavation Feasibility studies Foundations Geoengineering Geotechnical Engineering & Applied Earth Sciences Hydraulics Learning algorithms Learning behaviour Load distribution Machine learning Optimization Parameters Regression analysis Regression models Research Paper Sandy soils Screw conveyors Soft and Granular Matter Soil Soil Science & Conservation Solid Mechanics Support vector machines Torque Tunnel construction Tunneling Tunneling shields Tunnels Excavation behaviour Gradient boosting regression Shield tunnelling Machine learning Over-smoothing
ISSN:	1861-1125, 1861-1133
On-line prístup:	Získať plný text
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