Novel hybrid SCA-XGB model for compressive strength of concrete at elevated temperatures
Author:
Publisher
Springer Science and Business Media LLC
Subject
Civil and Structural Engineering
Link
https://link.springer.com/content/pdf/10.1007/s42107-023-00874-0.pdf
Reference38 articles.
1. Abbas, H., Al-Salloum, Y. A., Elsanadedy, H. M., & Almusallam, T. H. (2019). ANN models for prediction of residual strength of HSC after exposure to elevated temperature. Fire Safety Journal, 106, 13–28. https://doi.org/10.1016/j.firesaf.2019.03.011
2. Ahmad, A., Ostrowski, K. A., Maślak, M., Farooq, F., Mehmood, I., & Nafees, A. (2021). Comparative study of supervised machine learning algorithms for predicting the compressive strength of concrete at high temperature. Materials, 14(15), 4222. https://doi.org/10.3390/ma14154222
3. An, J., Mikhaylov, A., & Richter, U. H. (2020). Trade war effects: evidence from sectors of energy and resources in Africa. Heliyon, 6(12), e05693. https://doi.org/10.1016/j.heliyon.2020.e05693
4. Chan, Y. N., Luo, X., & Sun, W. (2000). Compressive strength and pore structure of high-performance concrete after exposure to high temperature up to 800 °C. Cement and Concrete Research, 30(2), 247–251. https://doi.org/10.1016/S0008-8846(99)00240-9
5. Chen, T., & Guestrin, C. (2016). XGBoost: a scalable tree boosting system. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (Vol. 13–17-Augu, pp. 785–794). New York, NY, USA: ACM. https://doi.org/10.1145/2939672.2939785
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