Learned Prediction of Compressive Strength of GGBFS Concrete Using Hybrid Artificial Neural Network Models

A new hybrid intelligent model was developed for estimating the compressive strength (CS) of ground granulated blast furnace slag (GGBFS) concrete, and the synergistic benefits of the hybrid algorithm as compared with a single algorithm were verified. While using the collected 269 data from previous...

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Detalles Bibliográficos
Autores principales: Han, In-Ji, Yuan, Tian-Feng, Lee, Jin-Young, Yoon, Young-Soo, Kim, Joong-Hoon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6888290/
https://www.ncbi.nlm.nih.gov/pubmed/31717660
http://dx.doi.org/10.3390/ma12223708

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6888290/
https://www.ncbi.nlm.nih.gov/pubmed/31717660
http://dx.doi.org/10.3390/ma12223708

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