Forecasting compressive strength and electrical resistivity of graphite based nano-composites using novel artificial intelligence techniques

To produce highly effective electrically conductive cementitious composites and advance non-destructive structural-health monitoring techniques, graphite-based nanomaterials (GrNs) are viable conductive fillers. A comprehensive database was created for CS and ER pertinent to GrNCC’s experimental stu...

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Autors principals:	Hisham Alabduljabbar, Muhammad Nasir Amin, Sayed M. Eldin, Muhammad Faisal Javed, Rayed Alyousef, Abdeliazim Mustafa Mohamed
Format:	Artigo
Idioma:	Inglês
Publicat:	Elsevier 2023-07-01
Col·lecció:	Case Studies in Construction Materials
Matèries:	Graphene Nanoparticles Compressive strength Electrical resistivity Machine learning (ML)
Accés en línia:	http://www.sciencedirect.com/science/article/pii/S221450952300027X
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