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Paper: Supervised Machine Learning Techniques to the Prediction of Tunnel Boring Machine Penetration Rate

Hai Xu , Jian Zhou (School of Resources and Safety Engineering, Central South University, Changsha 410083, China)

Panagiotis G. Asteris (Computational Mechanics Laboratory, School of Pedagogical and Technological Education, 14121 Heraklion, Athens, Greece)

Danial Jahed Armaghani (Institute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam)

Mahmood Md Tahir (UTM Construction Research Centre, Institute for Smart Infrastructure and Innovative Construction (ISIIC), School of Civil Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru 81310, Malaysia)

[ Modified to conform group and site rules. Please check group description - Tunnel Technologies group moderator]

Received: 14 July 2019; Accepted: 28 August 2019; Published: 6 September 2019

[Modified to conform group and site rules. Please check group description - Tunnel Technologies group moderator]

Paper:

https://www.mdpi.com/2076-3417/9/18/3715/pdf

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