Predicting the compressive strength of sulfur concrete using soft computing techniques
Author:
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Mechanics of Materials,General Materials Science
Link
https://link.springer.com/content/pdf/10.1007/s41939-023-00223-3.pdf
Reference65 articles.
1. ACI. ACI 548.2R-93 (1998) Guide for Mixing and Placing Sulfur Concrete in Construction. American Concrete Institute Committee: USA.
2. Ahmad A et al (2021) Prediction of compressive strength of fly ash based concrete using individual and ensemble algorithm. Materials 14(4):1–21. https://doi.org/10.3390/ma14040794
3. Ahmad A et al (2022) Compressive strength prediction of fly ash-based geopolymer concrete via advanced machine learning techniques. Case Stud Const Mater 16:1–16. https://doi.org/10.1016/j.cscm.2021.e00840
4. Ahsan Gulzar M et al (2021) An investigation on recycling potential of sulfur concrete. J Build Eng 38:1–9. https://doi.org/10.1016/j.jobe.2021.102175
5. AliKhan M et al (2021a) Application of gene expression programming (GEP) for the prediction of compressive strength of geopolymer concrete. Materials 15(5):1–21. https://doi.org/10.3390/ma14051106
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