The force analysis for large-span overhanging the SRC beam sections based on machine learning

Many different machine learning algorithms have been developed and implemented in a variety of programming languages over the past 20 years. Some optimization models (Artificial Neural Network (ANN) and Genetic Algorithm (GA)) for the design of large overhanging steel and concrete beams have been proposed. Their ultimate aim is to optimize the material cost in making the beam satisfy conditions of strength, deformation etc. and to give advice to engineers when first selecting a section for such beams. In this study, this essay aimed at demonstrating of adapting scikit-learn to predict the compressive strength and using a simple genetic algorithm for the optimal selection of large-span overhanging the SRC beam sections.