Experience in industrial plant model development using large-scale artificial neural networks

Artificial neural networks (ANN) are used for modeling the behavior of real-life systems. However, most of the published papers deal with small- or medium-scale systems. One of the possible reasons, the slow learning or nonconvergence of large-scale networks, can now be overcome by the use of the nonrandom initial connection weight algorithm. The developed ANN model can then be optimized, after the elimination of nonrelevant inputs and finding the necessary number of hidden-layer ''neurons.'' Causal relationships can be extracted from the ANN process model, and the reasons for deviations from the model-predicted behavior can be analyzed. This paper describes the application of large-scale ANN in modeling of industrial plants. (C) Elsevier Science Inc. 1997.