Exploring the interrelationships between composition, rheology, and compressive strength of self-compacting concrete: An exploration of explainable boosting algorithms

Exploring the interrelationships between composition, rheology, and compressive strength of self-compacting concrete: An exploration of explainable boosting algorithms

This study introduces a novel methodology for enhancing the compressive strength of self-compacting concrete (SCC) via the use of the Explainable Boosting Machine (EBM), a sophisticated and interpretable machine learning algorithm. It presents a data-driven model that aims to accurately predict the...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Sarmed Wahab, Babatunde Abiodun Salami, Ali H. AlAteah, Mohammed M.H. Al-Tholaia, Turki S. Alahmari
Μορφή: Άρθρο
Γλώσσα:English
Έκδοση: Elsevier 2024-07-01
Σειρά:Case Studies in Construction Materials
Θέματα:
Self-compacting concrete
Compressive strength
Machine learning
Ensemble algorithms
Explainable boosting machine
Διαθέσιμο Online:http://www.sciencedirect.com/science/article/pii/S2214509524002353

Διαδίκτυο

http://www.sciencedirect.com/science/article/pii/S2214509524002353

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