In-Depth Analysis of Cement-Based Material Incorporating Metakaolin Using Individual and Ensemble Machine Learning Approaches

• Published in: Materials Vol. 15; no. 21; p. 7764
• Main Authors: Bulbul, Abdulrahman Mohamad Radwan, Khan, Kaffayatullah, Nafees, Afnan, Amin, Muhammad Nasir, Ahmad, Waqas, Usman, Muhammad, Nazar, Sohaib, Arab, Abdullah Mohammad Abu
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 03.11.2022; MDPI
• Subjects: Algorithms; Analysis; Cement hydration; Compressive strength; Concrete; Concrete construction; Concrete properties; Data points; Decision trees; Environment models; Environmental effects; Environmental impact; Forecasts and trends; Investigations; Machine learning; Mechanical properties; Metakaolin; Multilayer perceptrons; Neural networks; Optimization techniques; Parameters; Prediction models; Silica fume; Superplasticizers; Variables

In recent decades, a variety of organizational sectors have demanded and researched green structural materials. Concrete is the most extensively used manmade material. Given the adverse environmental effect of cement manufacturing, research has focused on minimizing environmental impact and cement-b...