Application of Probabilistic Neural Network in the Mill Pacing Evaluation of Hot Strip Mill
XU Zu-hong1，CHEN Chao-chao2，SHAO Jian2
（1. 2250mm Hot Strip Mill，Hunan Valin Lianyuan Iron and Steel Co．， Ltd．， Loudi 417009， Hunan， China 2. National Engineering Research Center for Advanced Rolling Technology，University of Science and Technology Beijing， Beijing 100083， China）
Abstract：The probabilistic neural network (PNN) and prediction thought are combined to evaluate mill pacing of hot rolling mill．A model based on PNN is established．To verify the validity of the model and predicted results，the model is applied to practical production of a hot strip mill and compared with the BP network．The results prove that the model has the advantage of simple structure，fast calculation，high prediction accuracy and strong generalization ability，which is able to substitute for the existing evaluation model based on the empirical formula and empirical data．Meanwhile，it provides a reference for the optimization of the mill pacing and production efficiency, so it has an important practical significance．
徐祖宏，陈超超，邵健. 概率神经网络在热轧轧制节奏评价中的应用[J]. 中国冶金, 2014, 24(3): 27-30.
XU Zu-hong，CHEN Chao-chao，SHAO Jian. Application of Probabilistic Neural Network in the Mill Pacing Evaluation of Hot Strip Mill. China Metallurgy, 2014, 24(3): 27-30.
2014, Vol. 24 
