基于数据挖掘技术的带钢力学性能质量模型  

Quality Model of Mechanical Properties of Hot-rolled Steel Strip Established with Data Mining Technology

作　　者：王丹民[1] 李华德[1] 李擎[1] 

机构地区：[1]北京科技大学信息工程学院,北京100083

出　　处：《计算机工程》2007年第1期244-246,共3页Computer Engineering

摘　　要：介绍了建立热轧带钢力学性能质量模型的数据挖掘过程。用普通神经网络建立起由工艺参数预测力学性能的质量模型,模型预测结果的5%命中率是0.508。提出了一种新的建模方法──逐层逼近法,并用它建立起质量模型,预测结果的5%命中率达到0.721,完全可以满足现实生产需要。The data mining process of establishing the quality model is introduced, that could predict the mechanical properties of hot-rolled steel strip with the technological parameter. The quality model whose hit ratio of 5% deviation reach 0.508 is established by applying the technology of basic artificial neural network. The quality model whose hit ratio of 5% deviation reach 0.721 is established by applying the technology of layer-of-layer impending, and this model could meet current industrial demand fully.

关 键 词：数据挖掘 人工神经网络 力学性能 

分 类 号：TG335.5[金属学及工艺—金属压力加工]