Textile plant modeling using Recurrent Neural Networks

The aim of this paper is to understand the importance of modeling the dynamic of industrial systems using Recurrent Neural Network (RNN) and report the results obtained by training the RNN on a textile process to identify the relationship between yarn color and fabric color. The importance of RNN can be highlighted by the fact that the information about the underlying dynamics of such systems is not available. The dynamics can only be observed with the help of certain measurable variables. In this context, Recurrent Neural Network based approach is a powerful tool with promising results. In conventional Neural Network based approaches, periodic training is required. The time between retraining is still an open issue.