Predicting Compressive Strength of 3D Printed Mortar in Structural Members Using Machine Learning

Machine learning is the discipline of commands in computer machine to predict and expect results real application currently most promising simulation artificial intelligence. This paper aims at using different algorithms calculate compressive strength extrusion 3DP concrete (cement mortar). The investigation carried out multi-objective grasshopper optimization algorithm (MOGOA) neural network (ANN). Given that accuracy a method depends on number data records, for 3D printing, this limited few years study, work develops new by combining both methodologies into an ANNMOGOA approach 3D-printed concrete. Some iteration process are achieved.