Bayesian neural networks on the inference of distillation product quality

The control of the distillation process in oil refineries requires the evaluation of product quality throughout the operation of the plant. This paper uses Bayesian neural networks, combined to several pre-processing and variable selection techniques, to develop systems for inferencing the quality of distillation products, for REPAR refinery (Refinaria do Parana), operated by PETROBRAS.