Prediction of Displacement and Stress Values of Composite Materials Under Load with Machine Learning Models

In this study, the determination of displacement and stress values under certain load glass fiber epoxy resin laminated reinforced composite materials by using machine learning models is targeted. scope modelling done changing material properties varied laminations samples via Ansys software a tensile force implemented in order to receive total deformation Von Misses stresses creation dataset completed. The robust linear regression Gaussian process from algorithms are used predict determine training testing with created. As result, predicted obtained trained tested real compared. Additionally, consideration model parameters for both models, evaluation true responses correct prediction/determination done. According results, determined as better related study.