Abstract:
According to the inherent shortcomings of traditional rolling force models,an ELM (extreme learning machine) model based on grey correlation analysis is proposed. First,the correlation analysis of input factors is carried out by grey correlation analysis in order to improve model performance. Second,the 10-fold cross validation method is applied to determining the node number in the hidden layer of the ELM model,and the rolling force prediction model is then established. The network is trained and tested with field data and compared with traditional models. Simulation results show that the model proposed can predict rolling force quickly and accurately,and is able to meet the requirements for online prediction in actual rolling processes.