Extruder Modelling: A Comparison of two Paradigms
Chemical Engineering, Newcastle University, UK, (1996)Abstract
In this contribution two data based modelling
paradigms are compared. Using measurements from an
industrial plasticating extrusion process, a locally
recurrent neural network and a genetic programming
algorithm are used to develop inferential models of the
polymer viscosity. It is demonstrated that both
techniques produce adequate non-linear dynamic
inferential models. However, for this application the
genetic programming technique adopted produces models
that perform better than the locally recurrent neural
network. Moreover, the final model produced by the
algorithm has a simple transparent structure.