Comparison of performance prediction of TBM in two rock conditions using different machine learning techniques

Abstract Accurate estimation of the rate of penetration (ROP) is essential for planning and optimizing tunnel boring machine (TBM) operations. Unlike previous studies that evaluated each project independently, this study develops a unified cross-project prediction framework using geotechnical datase...

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Autors principals:	Rui Yong, Sujith Mangalathu, Pengpeng Ni, Changshuo Wang
Format:	Artigo
Idioma:	Inglês
Publicat:	Springer 2025-12-01
Col·lecció:	Geomechanics and Geophysics for Geo-Energy and Geo-Resources
Matèries:	Tunnel boring machine (TBM) Rate of penetration Machine learning Performance prediction
Accés en línia:	https://doi.org/10.1007/s40948-025-01091-6
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