Input Variable Effects on TBM Penetration Rate: Parametric and Machine Learning Models

In this study, linear and nonlinear parametric models (M1–M6) were jointly evaluated alongside machine learning (ML)-based approaches to achieve reliable and interpretable prediction of the penetration rate (ROP) of tunnel boring machines (TBMs). The analyses incorporate key geomechanical and struct...

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Detalles Bibliográficos

Autores principales:	Halil Karahan, Devrim Alkaya
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	MDPI AG 2026-01-01
Colección:	Applied Sciences
Materias:	TBM penetration rate parametric and machine learning models support vector machines generalized additive models Jacobian-based elasticity PDP/ALE analysis
Acceso en línea:	https://www.mdpi.com/2076-3417/16/3/1301
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!