Compressive strength estimation of rice husk ash-blended high-strength concrete using diffGrad-optimized deep learning approach
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/s41939-023-00315-0.pdf
Reference75 articles.
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2. Aggarwal CC (2018) Neural networks and deep learning. Springer, Berlin
3. Al-Hashem MN et al (2022) Predicting the compressive strength of concrete containing fly ash and rice husk ash using ANN and GEP models. Materials 15:7713
4. Alidoust P, Goodarzi S, Tavana Amlashi A, Sadowski Ł (2023) Comparative analysis of soft computing techniques in predicting the compressive and tensile strength of seashell containing concrete. Eur J Environ Civ Eng 27:1853–1875. https://doi.org/10.1080/19648189.2022.2102081
5. Al-Shamiri AK, Kim JH, Yuan T-F, Yoon YS (2019) Modeling the compressive strength of high-strength concrete: an extreme learning approach. Constr Build Mater 208:204–219. https://doi.org/10.1016/j.conbuildmat.2019.02.165
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