Predicting properties for secondary aging of 7055 Al alloy based on artificial neural networks
Hai Li · The Chinese Journal of Nonferrous Metals · 2006
A model was developed for modeling the correlation between process parameters of second aging treatment and properties of 7055 Al alloy by applying the artificial neural networks(ANN).According to the feature of second aging,the process parameters were preliminary aging temperature,preliminary aging time,second aging temperature and second aging time.The model was based on error back-propagation(BP) algorithm and trained by Levenberg-Marquardt training algorithm.After the ANN model was trained successfully,the model achieved a very good performance.The results show that the model has high precision and good generalization performance,and can be successfully used to predict and analyze the influence of secondary aging treatment on the mechanical properties of 7055 Al alloy.