Ozerdem, Mehmet SiracKolukisa, Sedat2024-04-242024-04-2420090264-12751873-4197https://doi.org/10.1016/j.matdes.2008.05.019https://hdl.handle.net/11468/15800In this study, an artificial neural network approach is employed to predict the mechanical properties of Cu-Sn-Pb-Zn-Ni cast alloys. In artificial neural network (ANN), multi layer perceptron (MLP) architecture with back-propagation algorithm is utilized. In Artificial Neural Network training module, Cu-Sn-Pb-Zn-Ni (wt%) contents were employed as input while yield strength, tensile strength and elongation were employed 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 of the study neural network was found successful for the prediction of yield strength, tensile strength and elongation of Cu-Sn-Pb-Zn-Ni alloys. (C) 2008 Elsevier Ltd. All rights reserved.eninfo:eu-repo/semantics/closedAccessArtificial Neural NetworkPrediction Of Mechanical PropertiesCu-Sn-Pb-Zn-Ni Cast AlloysArticle303764769WOS:0002628691000492-s2.0-5714911863210.1016/j.matdes.2008.05.019Q1Q2