Non-destructive Tests for Estimating the Tensile Strength in Concrete with Deep Learning
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-21735-7_91
Reference18 articles.
1. Guzmán Torres, J.A., Mota, F.J.D., Guzmán, E.M.A., Molina, W.M., Ruiz, G.T.: A review of concrete performance employing a starch as addition using several regression techniques. In: Advanced Materials Research, vol. 1160, pp. 1–14. Trans Tech Publications Ltd. (2021)
2. Guzmán Torres, J.A., et al.: Prediction of the tensile strength and electrical resistivity of concrete with organic polymer and their influence on carbonation using data science and a machine learning technique. In: Key Engineering Materials, vol. 862, pp. 72–77. Trans Tech Publications Ltd. (2020)
3. Guzmán-Torres, J.A., Zalapa-Damian, A., Domínguez-Mota, F.J., Alonso-Guzmán, E.M.: Data science and machine learning technique for predicting electrical resistivity in recycled concrete with nopal as addition. In: Advanced Engineering Forum, vol. 40, pp. 43–62. Trans Tech Publications Ltd. (2021)
4. Rafiei, M.H., Adeli, H.: A novel machine learning-based algorithm to detect damage in high-rise building structures. Struct. Des. Tall Spec. Build. 26(18), e1400 (2017)
5. Guzmán-Torres, J.A., Domínguez-Mota, F.J., Alonso-Guzmán, E.M.: Estimating the flexural strength of concrete using compressive strength as input value in a deep learning model. In: IOP Conference Series: Materials Science and Engineering, vol. 1150, no. 1, p. 012019. IOP Publishing
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