NEURAL COMPUTING AND APPLICATIONS, cilt.4, sa.1, ss.10-20, 2024 (SCI-Expanded)
In the reinforced concrete (RC) columns which are exposed extreme loads such as earthquake effects, the plastic hinge
length can be defined as the length of the region where flexural moments exceed the yielding capacity, and the plastic
deformations are concentrated. More accurate estimation of plastic hinge length increases the reliability of the seismic
design. However, a sensitivity prediction of plastic hinge length is difficult due to a large number of model parameters.
Therefore, this study aims to predict the plastic hinge length using the gene expression programming (GEP). An experimental database of 133 RC columns gathered from the literature was utilized for prediction with GEP. The results of GEP
model are statistically compared with those of 13 models existing in the literature proposed by various researchers. The
comparison results reveal that the proposed GEP-based formulation has the best efficiency among all models. Furthermore,
a sensitivity analysis and parametric study are conducted to identify the most influential parameters affecting the GEP
formulation.