Data-driven models of crude distillation units for production planning and for operations monitoring

This work develops best practices for building consistent data-driven CDU models for production planning and for monitoring. Prior knowledge-based transformations of raw data are shown to be essential to achieve high model accuracy. Data-driven SOM-ResNet and PCA-ResNet deep models, feedforward neural network (FNN), partial least-squares (PLS), and least absolute shrinkage and selection operator (LASSO) are studied. Instead of increasing the …