1. School of Materials Science and Engineering， University of Science and Technology Beijing， Beijing 100083， China；2. Angang Co., Ltd., Anshan Iron and Steel Group Corporation, Anshan 114011, Liaoning, China； 3. School of Mechanical Engineering， University of Science and Technology Beijing， Beijing 100083， China
Abstract：In view of intrinsic imperfection of traditional models of rolling force, in order to improve the prediction precision of rolling force of tandem cold mill, a sort of artificial neural networks with RBF algorithm was used to predict yield stress of cold rolled steel strip，and then this value was used to calculate rolling force with traditional mathematical model; and then the stand network（RBF type）, speed network(RBF type) were combined to correct calculated rolling force. Application of this method indicated that it has a final error within ±6.5%.
张俊明;刘军;康永林;杨荃. 应用RBF神经网络预测冷连轧机轧制力[J]. 钢铁, 2007, 42(8): 46-0.
ZHANG Junming;LIU Jun;KANG Yonglin;YANG Quan. Application of RBF Neural Networks to Prediction of Rolling Force of Tandem Cold Mill. Iron and Steel, 2007, 42(8): 46-0.
2007, Vol. 42 
