基于RBF神经网络的挤出吹塑中型坯尺寸的预测  

Prediction of Parison Dimension Based on RBF Neural Network in Plastics Extrusion Blow Molding

作　　者：杨艳娟[1] 黄汉雄[1] 

机构地区：[1]华南理工大学工业装备与控制工程学院塑料橡胶装备及智能化研究中心,广东广州510640

出　　处：《塑料工业》2006年第10期36-38,共3页China Plastics Industry

基　　金：华南理工大学自然科学基金

摘　　要：在利用BP神经网络预测挤出吹塑中型坯尺寸工作的基础上,采用径向基神经网络(RBF)来预测挤出吹塑中型坯尺寸,并与BP神经网络的预测结果进行了比较。结果表明,虽然RBF与BP神经网络均能较好地预测挤出吹塑中型坯尺寸,RBF网络的训练时间比BP少很多,只是BP的0.7%。Based on the prediction of the parison dimension in plastics extrusion blow molding by BR neural network, RBF neural network was applied to predict the parison dimension in plastics extrusion blow molding, and the results of RBF was compared with that by BP. The results showed both RBF and BP could predict the parison dimensions well, but the training time of RBF was much shoter, being only 0.7 % of that of BP.

关 键 词：挤出吹塑 型坯成型 型坯尺寸 RBF神经网络 

分 类 号：TQ320.662[化学工程—合成树脂塑料工业]