ABSTRACT
Concrete-filled steel tubular columns have gained popularity in construction in recent decades as they offer the benefit of constituent materials and cost-effectiveness. Fire-resistance rate is an essential parameter to measure for the concrete-filled steel tubular columns. In this chapter, gene expression programming is used to propose a new framework for the fire-resistance rate, depending on seven parameters. A large dataset is used to predict the fire-resistance rate. The model’s performance, accuracy, and efficiency are calculated along with multiple statistical criteria and graphical illustrations, based on the gene expression programming approach using GeneXprotools 5.0. The chapter highlights the benefit of gene expression programming in developing a new model for complex situations like fire-resistance rate in concrete-filled steel tubular columns.
