中國有色金屬學(xué)報(bào)(英文版)
Transactions of Nonferrous Metals Society of China
| Vol. 10 No. 2 April 2000 |
LIU Han-wu(劉漢武)3, CUI Jian-zhong(崔建忠)3, BA Li-min(巴立民)4
（1. Department of Mechanical Engineering, Tsinghua University, Beijing100084, P.R.China;
2. Department of Metal Forming, University of Science and Technology Beijing,
Beijing100083, P.R.China;
3. Department of Metal Forming, Northeastern University, Shenyang110006, P.R.China;
4. Anshan Automobile Fittings Factory, Anshan 114014, P.R.China）
Abstract:Artificial neural networks were successfully used to research the modeling of aluminum solid fraction, preheat temperature of steel plate, preheat temperature of dies, free diffusing time before pressing and the interfacial shear strength in steel-mushy aluminum pressing bonding. Further more, the optimum bonding parameters for the largest interfacial shear strength were also optimized with a genetic algorithm.
Key words: artificial neural networks; steel-mushy aluminum bonding; genetic algorithm
