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Redouane Rebouh

The following bibliography contains all publications indexed in this database that are linked with this name as either author, editor or any other kind of contributor.

  1. Benzaamia, Ali / Ghrici, Mohamed / Rebouh, Redouane / Pilakoutas, Kypros / Asteris, Panagiotis G. (2024): Predicting the compressive strength of CFRP-confined concrete using deep learning. In: Engineering Structures, v. 319 (November 2024).

    https://doi.org/10.1016/j.engstruct.2024.118801

  2. Benzaamia, Ali / Ghrici, Mohamed / Rebouh, Redouane / Zygouris, Nikos / Asteris, Panagiotis G. (2024): Predicting the shear strength of rectangular RC beams strengthened with externally-bonded FRP composites using constrained monotonic neural networks. In: Engineering Structures, v. 313 (August 2024).

    https://doi.org/10.1016/j.engstruct.2024.118192

  3. Kellouche, Yasmina / Boukhatem, Bakhta / Ghrici, Mohamed / Rebouh, Redouane / Zidol, Ablame (2021): Neural network model for predicting the carbonation depth of slag concrete. In: Asian Journal of Civil Engineering, v. 22, n. 7 (September 2021).

    https://doi.org/10.1007/s42107-021-00390-z

  4. Boukhatem, Bakhta / Rebouh, Redouane / Zidol, Ablam / Chekired, Mohamed / Tagnit-Hamou, Arezki (2019): An intelligent hybrid system for predicting the tortuosity of the pore system of fly ash concrete. In: Construction and Building Materials, v. 205 (April 2019).

    https://doi.org/10.1016/j.conbuildmat.2019.02.005

  5. Rebouh, Redouane / Boukhatem, Bakhta / Ghrici, Mohamed / Tagnit-Hamou, Arezki (2017): A practical hybrid NNGA system for predicting the compressive strength of concrete containing natural pozzolan using an evolutionary structure. In: Construction and Building Materials, v. 149 (September 2017).

    https://doi.org/10.1016/j.conbuildmat.2017.05.165

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