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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。
Based on the experimental data obtained from the Gleeble_1500 thermal simulator, the prediction model of the deformation resistance of 50CrV4 steel with strain, strain rate and temperature was established by artificial neural network method. Compared with multivariate nonlinear regression model, the proposed model has higher accuracy .