A neural network meta-model of roll-drafting process

This paper presents a neural network based meta-model of the roll-drafting process which was elaborated on the basis of a discrete-event simulation model presented previously. The GRNN, RBF, MLP3, and MLP4 networks were trained, tested and compared. The training set for the neural networks was obtained from the discrete event simulation model, which is characterized by a beta-distributed velocity change point and satisfies the first and second limit schemes of the roll-drafting process. A comparative analysis of the four different types of meta-models led to the conclusion that the MLP4 meta-model provides the best prediction of roll-drafted fibrous material irregularity. Testing of the developed meta-model has shown a high-level coincidence between this meta-model and the DES model of the roll-drafting process.