A PCA based output integrated recurrent neural network for dynamic process modeling

摘要

Combining data analysis and neural network techniques, this paper proposes a novel modeling method, the principal component analysis (PCA) based output integrated recurrent neural network (OIRNN). The modeling and training algorithm are presented and demonstrated for a typical chemical process. It is characteristic of rational model structure and good prediction of the non-linear dynamic behaviors.