Machine Learning Applications in Concrete Strength Prediction - Nadeemallah, Altamashuddin Khan;Basha, S.I. Manjur
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Machine Learning Approaches to Concrete Strength Prediction combines traditional engineering with modern data science, reshaping how we predict concrete strength. Focusing on concrete mixes that use sand, manufactured sand (M-sand), and laterite soil as fine aggregates, this book provides a practical guide to machine learning techniques like Linear Regression, Decision Trees, Random Forest, Support Vector Regression, and Gradient Boosting. With clear explanations and a real-world case study, it equips readers with the knowledge to apply data-driven approaches in construction.

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Produktbeschreibung
Machine Learning Approaches to Concrete Strength Prediction combines traditional engineering with modern data science, reshaping how we predict concrete strength. Focusing on concrete mixes that use sand, manufactured sand (M-sand), and laterite soil as fine aggregates, this book provides a practical guide to machine learning techniques like Linear Regression, Decision Trees, Random Forest, Support Vector Regression, and Gradient Boosting. With clear explanations and a real-world case study, it equips readers with the knowledge to apply data-driven approaches in construction.
Autorenporträt
The authors, Dr. Altamashuddin Khan Nadimalla and Dr. S.I. Manjur Basha, serve as Associate Professor of Civil Engineering and Professor of Electronics and Communication Engineering, respectively, at Bearys Institute of Technology in Mangalore.