A novel Hybrid XGBoost Methodology in Predicting Penetration Rate of Rotary Based on Rock-Mass and Material Properties
Crossref DOI link: https://doi.org/10.1007/s13369-023-08360-0
Published Online: 2023-10-28
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Kazemi, Mohammad Mirzehi Kalate
Nabavi, Zohre
Armaghani, Danial Jahed
Funding for this research was provided by:
University of Technology Sydney
Text and Data Mining valid from 2023-10-28
Version of Record valid from 2023-10-28
Article History
Received: 17 June 2023
Accepted: 27 September 2023
First Online: 28 October 2023