Predicting TBM penetration rate in hard rock condition: A comparative study among six XGB-based metaheuristic techniques

Predicting TBM penetration rate in hard rock condition: A comparative study among six XGB-based metaheuristic techniques

A reliable and accurate prediction of the tunnel boring machine (TBM) performance can assist in minimizing the relevant risks of high capital costs and in scheduling tunneling projects. This research aims to develop six hybrid models of extreme gradient boosting (XGB) which are optimized by gray wol...

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Bibliographic Details
Main Authors: Jian Zhou, Yingui Qiu, Danial Jahed Armaghani, Wengang Zhang, Chuanqi Li, Shuangli Zhu, Reza Tarinejad
Format: Article
Language:English
Published: Elsevier 2021-05-01
Series:Geoscience Frontiers
Subjects:
TBM penetration rate
Hard rock
XGB-based hybrid model
Predictive model
Metaheuristic optimization
Online Access:http://www.sciencedirect.com/science/article/pii/S1674987120302231

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http://www.sciencedirect.com/science/article/pii/S1674987120302231

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