A new prediction model for the load capacity of castellated steel beams

In this study, a robust variant of genetic programming, namely gene expression programming (GEP), is utilized to build a prediction model for the load capacity of castellated steel beams. The proposed model relates the load capacity to the geometrical and mechanical properties of the castellated beams. The model is developed based on a reliable database obtained from the literature. To verify the applicability of the derived model, it is employed to estimate the load capacity of parts of the test results that were not included in the modeling process. The external validation of the model was further verified using several statistical criteria recommended by researchers. A multiple least squares regression analysis is performed to benchmark the GEP-based model. A sensitivity analysis is further carried out to determine the contributions of the parameters affecting the load capacity. The results indicate that the proposed model is effectively capable of evaluating the failure load of the castellated beams. The GEP-based design equation is remarkably straightforward and useful for pre-design applications.

Research highlights
► A new prediction model is developed for the load capacity of castellated steel beams utilizing gene expression programming (GEP).
► The load capacity is formulated in terms of the geometrical and mechanical properties of the castellated beams.
► The validation of the model is verified using several statistical criteria recommended by researchers.
► The GEP-based design equation is remarkably straightforward, precise, and useful for pre-design applications.