Transactions of Nonferrous Metals Society of China The Chinese Journal of Nonferrous Metals

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Transactions of Nonferrous Metals Society of China

Vol. 21    No. 4    April 2011

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Improvement and application of neural network models in
 development of wrought magnesium alloys
LIU Bin1, TANG Ai-tao1, 2, PAN Fu-sheng1, 2, ZHANG Jing1, 2, PENG Jian 1, 2, WANG Jing-feng1, 2

1. College of Materials Science and Engineering, Chongqing University, Chongqing 400030, China;
2. National Engineering Research Center for Magnesium Alloys, Chongqing University,
Chongqing 400030, China

Abstract:Neural network models of mechanical properties prediction for wrought magnesium alloys were improved by using more reasonable parameters, and were used to develop new types of magnesium alloys. The parameters were confirmed by comparing prediction errors and correlation coefficients of models, which have been built with all the parameters used commonly with training of all permutations and combinations. The application was focused on Mg-Zn-Mn and Mg-Zn-Y-Zr alloys. The prediction of mechanical properties of Mg-Zn-Mn alloys and the effects of mole ratios of Y to Zn on the strengths in Mg-Zn-Y-Zr alloys were investigated by using the improved models. The predicted results are good agreement with the experimental values. A high strength extruded Mg-Zn-Zr-Y alloy was also developed by the models. The applications of the models indicate that the improved models can be used to develop new types of wrought magnesium alloys.


Key words: magnesium alloy; artificial neural network; model; mechanical property

ISSN 1004-0609
CN 43-1238/TG

ISSN 1003-6326
CN 43-1239/TG

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