Using Neural Networks to Predict the Hardness of Aluminum Alloys


  • B. Zahran Department of Computer Engineering, Al-Balqa Applied University, Jordan
Volume: 5 | Issue: 1 | Pages: 757-759 | February 2015 |


Aluminum alloys have gained significant industrial importance being involved in many of the light and heavy industries and especially in aerospace engineering. The mechanical properties of aluminum alloys are defined by a number of principal microstructural features. Conventional mathematical models of these properties are sometimes very complex to be analytically calculated. In this paper, a neural network model is used to predict the correlations between the hardness of aluminum alloys in relation to certain alloying elements. A backpropagation neural network is trained using a thorough dataset. The impact of certain elements is documented and an optimum structure is proposed


aluminum alloys, hardness, neural networks


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How to Cite

B. Zahran, “Using Neural Networks to Predict the Hardness of Aluminum Alloys”, Eng. Technol. Appl. Sci. Res., vol. 5, no. 1, pp. 757–759, Feb. 2015.


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