Abstract
Cold rolling is often carried out between the solid solution treatment and aging to assist in the aging hardening of Cu-Cr-Zr lead frame alloys. This paper presents the use of an artificial neural network(ANN) to model the non-linear relationship between parameters of rolling and aging with respect to hardness properties of Cu-Cr-Zr alloy. Based on the Gauss-Newton algorithm, Levenberg-Marquardt algorithm with high stability is deduced. High precision of the model is demonstrated as well as good generalization performance. The results show that the Levenberg-Marquardt(L-M) backpropagation(BP) algorithm of ANN system is effective for predicting and analyzing the hardness properties of Cu-Cr-Zr lead frame alloy.
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© 2005 Springer-Verlag Berlin Heidelberg
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Su, J., Li, H., Dong, Q., Liu, P. (2005). Modelling of Rolling and Aging Processes in Copper Alloy by Levenberg-Marquardt BP Algorithm. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539117_28
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DOI: https://doi.org/10.1007/11539117_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28325-6
Online ISBN: 978-3-540-31858-3
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