基于人工神經網絡的扁鋼軋制力模型

Modeling of the Rolling Force Based on Artificial Neural Networks

摘要: 根據BP人工神經網絡算法原理,結合某廠型鋼軋機軋制扁鋼時的軋制力實測數據,對扁鋼軋制力進行建模.結果表明,神經網絡用于軋制力建模是可行的,所建模型系統誤差<1%,模型計算值與實測值的偏差<4%,較好地反映了實際軋制過程的特征.

Abstract: Based on the principle of BP neural networks, the rolling force model is created after thoroughly analyzing and Processing the data of 400 nun mill. It states that the difference between the real value and the ours of the model is in order of 4 percent. The model on basis of BPNN is Practical and it reflects the real feature of the rolling process.