Artificial neural network approach to predict the electrical conductivity and density of Ag–Ni binary alloys

In this study, artificial neural network (ANN) approach was done to predict electrical conductivity and density of silver–nickel binary alloys using a back-propagation neural network that uses gradient descent learning algorithm. In ANN training module, Ag% and Ni% (weight) contents were employed as input and electrical conductivity, calculated and typical density were used as outputs. ANN system was trained using the prepared training set (also known as learning set). After training process, the test data were used to check system accuracy. As a result the neural network was found successful for the prediction of electrical conductivity and density of silver nickel binary alloys.