摘要
人工神经网络技术应用于马氏体开始转变点的研究。利用人工神经网络的反向传播 (BP)算法 ,建立了材料的合金成分与马氏体开始转变点的网络模型 ,从而对马氏体开始转变点温度进行分析和预测 ,并与经验公式相比 ,该网络模型具有更高的精度 ,从而为预测马氏体开始转变点温度提供了新颖的方法。
The newly developed neural network technique was employed to study martensite start temperature.The backpropagating algorithm in artificial neural networks is used to build a model for the relationship between the alloy element and martensite start temperature.The results show that the similar values of martensite start temperature M s predicted by neural network model and measured by experiment can be obtained.The neural network model provides a new method for the prediction of M s.
出处
《材料热处理学报》
EI
CAS
CSCD
北大核心
2004年第6期104-106,共3页
Transactions of Materials and Heat Treatment