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1 s2.0 S0141029623002341 Main 1 by Rania Hamad is a document available to read on EtoBox.
This study addresses the complex shear behavior of circular concrete-filled tube (CCFT) members by utilizing artificial intelligence techniques, specifically Gaussian Processing Regression (GPR), Genetic Expression Programming (GEP), and Nonlinear Regression (NR), to propose reliable design models based on 141 experimental test results. The findings indicate that the data-driven models significantly improve the prediction accuracy of shear capacity compared to existing conservative design equations, with GP
- Author
- Rania Hamad
- Language
- EN