Supervised machine learning techniques to the prediction of tunnel boring machine penetration rate

Supervised machine learning techniques to the prediction of tunnel boring machine penetration rate

Predicting the penetration rate is a complex and challenging task due to the interaction between the tunnel boring machine (TBM) and the rock mass. Many studies highlight the use of empirical and theoretical techniques in predicting TBM performance. However, reliable performance prediction of TBM is...

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Bibliographic Details
Main Authors: Xu, Hai, Zhou, Jian, Asteris, Panagiotis G., Armaghani, Danial Jahed, Md. Tahir, Mahmood
Format: Article
Language:English
Published: MDPI AG 2019
Subjects:
TA Engineering (General). Civil engineering (General)
Online Access:http://eprints.utm.my/88666/1/MahmoodMdTahir2019_SupervisedMachineLearningTechniquestothePrediction.pdf

Internet

http://eprints.utm.my/88666/1/MahmoodMdTahir2019_SupervisedMachineLearningTechniquestothePrediction.pdf

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