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Hybrid ensemble soft computing approach for predicting penetration rate of tunnel boring machine in a rock environment

This study implements a hybrid ensemble machine learning method for forecasting the rate of penetration (ROP) of tunnel boring machine (TBM), which is becoming a prerequisite for reliable cost assessment and project scheduling in tunnelling and underground projects in a rock environment. For this pu...

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Autors principals: Abidhan Bardhan, Navid Kardani, Anasua GuhaRay, Avijit Burman, Pijush Samui, Yanmei Zhang
Format: Artigo
Idioma:Inglês
Publicat: Elsevier 2021-12-01
Col·lecció:Journal of Rock Mechanics and Geotechnical Engineering
Matèries:
Tunnel boring machine (TBM)
Rate of penetration (ROP)
Artificial intelligence
Artificial neural network (ANN)
Ensemble modelling
Accés en línia:http://www.sciencedirect.com/science/article/pii/S1674775521001281
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