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In the current study, aluminum-magnesium-titanium alloys were manufactured with sand casting method and the effects of titanium and magnesium on the ductility, porosity, hardness and density of these alloys were investigated. The influences of these elements were also studied using multi-layer perceptron neural network approach. Regression models were advanced to check both the performance and the reliability of the proposed neural network model. It was seen that linear correlation of all output values is highest than 90%. It was also observed that Mg has a greater effect than Al and Ti on the hardness and porosity values, whereas Al has more sensitivity on the ductility of alloys. [ABSTRACT FROM AUTHOR]