Cargando…
Application of Machine Learning Approaches to Predict the Strength Property of Geopolymer Concrete
Geopolymer concrete (GPC) based on fly ash (FA) is being studied as a possible alternative solution with a lower environmental impact than Portland cement mixtures. However, the accuracy of the strength prediction still needs to be improved. This study was based on the investigation of various types...
Autores principales: | Cao, Rongchuan, Fang, Zheng, Jin, Man, Shang, Yu |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8999160/ https://www.ncbi.nlm.nih.gov/pubmed/35407733 http://dx.doi.org/10.3390/ma15072400 |
Ejemplares similares
-
Prediction of Geopolymer Concrete Compressive Strength Using Novel Machine Learning Algorithms
por: Ahmad, Ayaz, et al.
Publicado: (2021) -
Artificial Intelligence Approaches for Prediction of Compressive Strength of Geopolymer Concrete
por: Dao, Dong Van, et al.
Publicado: (2019) -
Optimization of Alkaline Activator on the Strength Properties of Geopolymer Concrete
por: Shilar, Fatheali A., et al.
Publicado: (2022) -
Application of Gene Expression Programming (GEP) for the Prediction of Compressive Strength of Geopolymer Concrete
por: Khan, Mohsin Ali, et al.
Publicado: (2021) -
Practical Prediction Models of Tensile Strength and Reinforcement-Concrete Bond Strength of Low-Calcium Fly Ash Geopolymer Concrete
por: Luan, Chenchen, et al.
Publicado: (2021)