Predictive modelling of concrete compressive strength incorporating GGBS and alkali using a machine-learning approach
Author:
Publisher
Springer Science and Business Media LLC
Subject
Civil and Structural Engineering
Link
https://link.springer.com/content/pdf/10.1007/s42107-023-00805-z.pdf
Reference27 articles.
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3. Chaabene, W. B., Flah, M., & Nehdi, M. L. (2020). Machine learning prediction of mechanical properties of concrete: Critical review. Construction and Building Materials, 260, 119889.
4. Chithra, S., Kumar, S. S., Chinnaraju, K., & Ashmita, F. A. (2016). A comparative study on the compressive strength prediction models for HIGH-PERFORMANCE CONCRETE containing nano silica and copper slag using regression analysis and artificial neural networks. Construction and Building Materials, 114, 528–535.
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