基于BP神经网络的Fe81Ga19合金磁致伸缩性能研究  

Magnetostriction Properties of Fe81Ga19 Alloy Based on BP Neural Network

作　　者：李晓明[1] 

机构地区：[1]齐齐哈尔大学计算机与控制工程学院,黑龙江齐齐哈尔161006

出　　处：《热加工工艺》2013年第18期97-99,共3页Hot Working Technology

摘　　要：基于BP神经网络的Fe81Ga19合金磁致伸缩性能,在不同的晶体偏离角度、预压力和磁场强度下,得到了Fe81Ga19合金的磁致伸缩应变的实验值。以试凑法来确定BP网络的中间隐层,确定网络结构为3-9-1。预测结果表明,采用BP神经网络法,可预测Fe81Ga19合金的磁致伸缩应变,预测误差均低于6%。The magnetostriction properties of Fe81Ga19 alloy was investigated by using BP neural network. Under different crystal deviation angles, pre-pressures and magnetic field intensities, the experimental magnetostriction strain values of Fe81Ga19 alloy were measured. Using a trial and error method. The intermediate hidden layers were determined and the network structure on 3-9-1 was obtained. The predicted results show that BP neural network is a good method for predicting the magnetostriction strain of Fe81Ga19 alloy and the prediction errors is less than 6%.

关 键 词：Fe81Ga19合金 磁致伸缩应变 BP神经网络 

分 类 号：TG113.225[金属学及工艺—物理冶金]