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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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| Publicat a: | Materials (Basel) |
|---|---|
| Autors principals: | , , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
MDPI
2019
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6888290/ https://ncbi.nlm.nih.gov/pubmed/31717660 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/ma12223708 |
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