Compressive Strength Estimation of Geopolymer Composites through Novel Computational Approaches

The application of artificial intelligence approaches like machine learning (ML) to forecast material properties is an effective strategy to reduce multiple trials during experimentation. This study performed ML modeling on 481 mixes of geopolymer concrete with nine input variables, including curing...

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Detalles Bibliográficos
Autores principales: Amin, Muhammad Nasir, Khan, Kaffayatullah, Ahmad, Waqas, Javed, Muhammad Faisal, Qureshi, Hisham Jahangir, Saleem, Muhammad Umair, Qadir, Muhammad Ghulam, Faraz, Muhammad Iftikhar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9147713/
https://www.ncbi.nlm.nih.gov/pubmed/35632011
http://dx.doi.org/10.3390/polym14102128

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9147713/
https://www.ncbi.nlm.nih.gov/pubmed/35632011
http://dx.doi.org/10.3390/polym14102128

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