An innovative multi expression programming (MEP) approach is used to derive new predictive equations for tangent elastic modulus of normal strength concrete (NSC) and high strength concrete (HSC). Similar to several building codes, the modulus of elasticity of NSC and HSC is formulated in terms of concrete compressive strength. Furthermore, a generic model is developed for the estimation of the elastic modulus of both NSC and HSC. Comprehensive databases are gathered from the literature to develop the models. For more verification, a parametric analysis is carried out and discussed. The proposed formulas are found to be accurate for the prediction of the elastic modulus of NSC and HSC. The predictions made by the MEP-based models are more accurate than those obtained by the existing models.

This study presents a new empirical model to estimate the base shear of plane steel structures subjected to earthquake load using a hybrid method integrating genetic programming (GP) and simulated annealing (SA), called GP/SA. The base shear of steel frames was formulated in terms of the number of bays, number of storey, soil type, and situation of braced or unbraced. A classical GP model was developed to benchmark the GP/SA model. The comprehensive database used for the development of the correlations was obtained from finite element analysis. A parametric analysis was carried out to evaluate the sensitivity of the base shear to the variation of the influencing parameters. The GP/SA and classical GP correlations provide a better prediction performance than the widely used UBC code and a neural network-based model found in the literature. The developed correlations may be used as quick checks on solutions developed by deterministic analyses.

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