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...

書誌詳細
主要な著者:	Sarmed Wahab, Babatunde Abiodun Salami, Ali H. AlAteah, Mohammed M.H. Al-Tholaia, Turki S. Alahmari
フォーマット:	論文
言語:	English
出版事項:	Elsevier 2024-07-01
シリーズ:	Case Studies in Construction Materials
主題:	Self-compacting concrete Compressive strength Machine learning Ensemble algorithms Explainable boosting machine
オンライン･アクセス:	http://www.sciencedirect.com/science/article/pii/S2214509524002353

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