High strength concrete compressive strength prediction using an evolutionary computational intelligence algorithm
Author:
Publisher
Springer Science and Business Media LLC
Subject
Civil and Structural Engineering
Link
https://link.springer.com/content/pdf/10.1007/s42107-023-00746-7.pdf
Reference48 articles.
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2. Adamu, M., Haruna, S. I., Malami, S. I., Ibrahim, M. N., Abba, S. I., & Ibrahim, Y. E. (2021). Prediction of compressive strength of concrete incorporated with jujube seed as partial replacement of coarse aggregate: a feasibility of Hammerstein-Wiener model versus support vector machine. Modeling Earth Systems and Environment. https://doi.org/10.1007/s40808-021-01301-6
3. Adeniyi, D. A., Wei, Z., & Yongquan, Y. (2016). Automated web usage data mining and recommendation system using K-Nearest Neighbor (KNN) classification method. Applied Computing and Informatics, 12(1), 90–108. https://doi.org/10.1016/j.aci.2014.10.001
4. Al-Shamiri, A. K., Kim, J. H., Yuan, T. F., & Yoon, Y. S. (2019). Modeling the compressive strength of high-strength concrete: An extreme learning approach. Construction and Building Materials, 208, 204–219. https://doi.org/10.1016/j.conbuildmat.2019.02.165
5. Armaghani, D. J., & Asteris, P. G. (2021). A comparative study of ANN and ANFIS models for the prediction of cement-based mortar materials compressive strength. Neural Computing and Applications. https://doi.org/10.1007/s00521-020-05244-4
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