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Applied Sciences
Volume 14
Issue 21
10.3390/app14219925
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Journal: Appl. Sci., 2024
Volume: 14
Number: 9925

Article: Data-Driven Optimised XGBoost for Predicting the Performance of Axial Load Bearing Capacity of Fully Cementitious Grouted Rock Bolting Systems
Authors: by Behshad Jodeiri Shokri, Ali Mirzaghorbanali, Kevin McDougall, Warna Karunasena, Hadi Nourizadeh, Shima Entezam, Shahab Hosseini and Naj Aziz
Link: https://www.mdpi.com/2076-3417/14/21/9925

MDPI offers high quality article reprints with convenient shipping to destinations worldwide. Each reprint features a 270 gsm bright white cover and 105 gsm premium white paper, bound with two stitches for durability and printed in full color. The cover design is customized to your article and designed to be complimentary to the journal.

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