BP网络模型在含硼微合金钢奥氏体晶粒尺寸及道次间软化程度预测中的应用  

Study on the Model of Austenite Grain Size and Softening Fraction in Microalloyed Steel with Neural Networks

作　　者：李立新[1] 汪凌云[2] 

机构地区：[1]武汉科技大学,武汉430081 [2]重庆大学,重庆400044

出　　处：《大型铸锻件》2003年第1期10-12,共3页Heavy Casting and Forging

摘　　要：以实验数据为基础 ,建立了含硼微合金钢高温奥氏体晶粒尺寸及道次间软化程度与热加工工艺参数间的 BP网络 (人工神经网络 )模型。结果表明This paper has developed two BP network models relating austenite grain size and softening fraction with hot working parameters in microalloyed steel on the basis of experimental data in gleeble-1500 system.The results show that the BP network models are ideal for their higher forecasting accuracy.

关 键 词：BP网络模型 含硼微合金钢 奥氏体 晶粒尺寸 预测 软化 

分 类 号：TG306[金属学及工艺—金属压力加工] TP183[自动化与计算机技术—控制理论与控制工程]