Cargando…
Application of Artificial Intelligence to Evaluate the Fresh Properties of Self-Consolidating Concrete
This paper numerically investigates the required superplasticizer (SP) demand for self-consolidating concrete (SCC) as a valuable information source to obtain a durable SCC. In this regard, an adaptive neuro-fuzzy inference system (ANFIS) is integrated with three metaheuristic algorithms to evaluate...
Autores principales: | Feng, Yuping, Mohammadi, Masoud, Wang, Lifeng, Rashidi, Maria, Mehrabi, Peyman |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8432695/ https://www.ncbi.nlm.nih.gov/pubmed/34500974 http://dx.doi.org/10.3390/ma14174885 |
Ejemplares similares
-
Utilizing Artificial Intelligence to Predict the Superplasticizer Demand of Self-Consolidating Concrete Incorporating Pumice, Slag, and Fly Ash Powders
por: Liu, Jing, et al.
Publicado: (2021) -
The Effect of Fine and Coarse Recycled Aggregates on Fresh and Mechanical Properties of Self-Compacting Concrete
por: Nili, Mahmoud, et al.
Publicado: (2019) -
Evaluation of the Performance of a Composite Profile at Elevated Temperatures Using Finite Element and Hybrid Artificial Intelligence Techniques
por: Ding, Wangfei, et al.
Publicado: (2022) -
Effects of Different Mineral Admixtures on the Properties of Fresh Concrete
por: Khan, Sadaqat Ullah, et al.
Publicado: (2014) -
Durability of self-consolidating concrete containing natural waste perlite powders
por: El Mir, Abdulkader, et al.
Publicado: (2020)