Straightforward Prediction for Responses of the Concrete Shear Wall Buildings Subject to Ground Motions Using Machine Learning Algorithms

The prediction of responses the reinforced concrete shear walls subject to strong ground motions is critical in designing, assessing, and deciding recovery strategies. This study evaluates ability regression models a hybrid technique (ANN-SA model), artificial neural network (ANN), Simulated Annealing (SA), predict motions. To this end, four buildings (15, 20, 25, 30-story) with were analyzed OpenSees.150 seismic records are used generate comprehensive database input (characteristics records) output (responses). maximum acceleration, velocity, earthquake characteristics as predictors. Different machine learning used, accuracy identifying compared. sensitivity variables demand model investigated. It has been seen from results that ANN-SA reasonable prediction.