The rapidly solidified aging copper alloy by BP neural network

Rapid solidifiation is a kind of new process for enhancing the hardness and electrical conductivity of Cu-Cr-Zr copper alloy. The use of BP neural network (NN) is presented to model the non-linear relationship between parameters of age hardening processes and the mechanical and electrical properties...

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Bibliographic Details
Published in:Journal of Wuhan University of Technology. Materials science edition 2003-12, Vol.18 (4), p.50-53
Main Authors: Juan-hua, Su, Qi-ming, Dong, Ping, Liu, He-jun, Li, Bu-xi, Kang
Format: Article
Language:English
Subjects:
Age hardening
Aging (artificial)
Algorithms
Back propagation networks
Chromium
Copper
Copper base alloys
Electrical properties
Electrical resistivity
Neural networks
Process parameters
Rapid solidification
Studies
Zirconium base alloys
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Summary:Rapid solidifiation is a kind of new process for enhancing the hardness and electrical conductivity of Cu-Cr-Zr copper alloy. The use of BP neural network (NN) is presented to model the non-linear relationship between parameters of age hardening processes and the mechanical and electrical properties of rapdily solidified Cu-Cr-Zr alloy. The improved model is developed by the Levenberg-Marquardt training algorithm and the good generalization performance is demonstrated. So, an important foundation has been laid for optimisticaly controlling the rapidly solidified aging processes of Cu-Cr-Zr alloy.[PUBLICATION ABSTRACT]
ISSN:1000-2413
1993-0437
DOI:10.1007/BF02838391