Neural network prediction of transformation efficiency of DyFe2 alloy prepared by reduction-diffusion process

作者：Guo Guangsi^*; Cheng Yongjun; Hu Xiaomei; Ye Fei

来源：Rare Metal Materials and Engineering, 2007, 36(4): 721-723.

• neural network
• prediction
• DyFe2 alloy
• transformation efficiency

Based on the main experiment parameters of DyFe2 alloy preparation by reduction-diffusion process: reaction temperature, holding time, added quantity of Ca and particle size of Fe, the BP neural network was established and used to predicate the transformation efficiency of DyFe2 alloy. The neural network was simulated by 44 groups of experimental data and was tested. It has been proved that the neural network has good performance to predict the transformation efficiency of DyFe2 alloy. This design of neural network is able to shorten the time of experiment, reduce the experiment cost, and optimize the preparation processes.

• 出版日期2007-4
• 单位沈阳理工大学