摘要
以Ｇｌｅｅｂｌｅ＿１５００热模拟机得到的实验数据为基础，采用人工神经网络方法建立了５０ＣｒＶ４钢变形抗力与应变、应变速率和温度对应关系的预测模型，并与多元非线性回归模型比较，具有较高的精度。
On the basis of the data obtained on Gleeble1500 Thermal Simulator,the predicting models for the relation between flow stress and deformation strain,strain rate and temperature for 50CrV4 have been developed with Artificial Neural Network method.Comparison with nonlinear regression method,the neural network gives better results.
出处
《钢铁》
CAS
CSCD
北大核心
1998年第4期27-30,共4页
Iron and Steel
关键词
人工神经网络
变形抗力
热模拟机
合金钢
artificial neural network,flow stress,Gleeble1500 Thermal Simulator
