Finding correlations between engineering demand parameters and intensity measures through evolutionary polynomial regression

A critical issue in performance-based seismic assessment of structures and infrastructures is the development of reliable formulations able to correlate engineering demand parameters (EDPs) with given earthquake intensity measures (IMs). This task involves the following steps: i) selection of target cases-study and elaboration of the corresponding structural models, ii) preparation of the database collecting seismic records, iii) identification of candidate EDPs and IMs, iv) nonlinear dynamic analyses, v) numerical calibration of functional models able to correlate EDPs and IMs, vi) evaluation of the predictive capability of the developed models. Within this framework, the present paper exploits an advanced nonlinear regression method - named Evolutionary Polynomial Regression technique - in order to obtain several non-dominated models (according to the Pareto's dominance criterion) that predict EDPs as function of assigned IMs for fixed-base and base-isolated multi-storey reinforced concrete buildings subjected to ordinary and pulse-like ground motion.