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Prediction of rheological parameters of 3D printed polypropylene fiber-reinforced concrete (3DP-PPRC) by machine learning

Md Nasir Uddin, Faharidine Mahamoudou, Bo-Yu Deng, Moneef Mohamed Elobaid Musa, Landry Wilfried Tim Sob

2023Materials Today Proceedings18 citationsDOI

Topics & Concepts

PolypropyleneRheologyPython (programming language)Support vector machineMaterials scienceRandom forestMachine learningArtificial intelligenceRheometerComposite materialGradient boostingComputer scienceMathematicsProgramming languageInnovations in Concrete and Construction MaterialsInnovative concrete reinforcement materialsAdditive Manufacturing and 3D Printing Technologies
Prediction of rheological parameters of 3D printed polypropylene fiber-reinforced concrete (3DP-PPRC) by machine learning | Litcius