ANN Flexible Forecasting for the Adaptive Monitoring of a Multi-Tube Reactor

The paper presents a flexible artificial neural network (ANN) model, in order to support modifications of a complex input-output function that describes the catalyst monitoring process of a multi-tube reactor. The goal is to obtain a good accuracy of the predicted data by using an optimal ANN architecture and well-suited delay vectors. The research targets the implementation of an adaptive system, which can be periodically retrained, in order to continuously learn the latest evolution of the catalyst process.