Prediction of mechanical strength of magnesium alloy AZ31 with calcium addition using a neural network based model

Abstract The aim of the research is to develop a neural network model predict mechanical strength AZ31 magnesium alloy in addition with Calcium. This would help researchers or academicians fabricate AZ31+x wt. % Ca which finds more importance making biodegradable implants orthopedic surgery. As yield human bone lies between 104.9 – 114.3 MPa whereas for pure Mg it very lesser, needed make alloys suitable biomedical applications are be satisfied their properties and biocompatibility. An artificial network-based used compositions Al, Zn, Mn as countable parts various proportions. twenty different cast were training prediction desired using Artificial Neural Network outputs compared experimental results. results show that Levenberg-Marquardt (LM) algorithm serves better AZ31+1 Ca. Also found significant at 90%, 95% 99% confidence limits.