Replication data for "Predicting Transfer Learning Suitability in ANN-based Control of FOPDT Industrial Processes"

This data repository supports the in review publication titled "Predicting Transfer Learning Suitability in ANN-based Control of FOPDT Industrial Processes" part of the E-TROTLE project. This project is funded under MCIN/AEI/10.13039 /501100011033 project TED2021-129134B-I00 co-funded with the European Union ‘‘NextGenerationEU’’/PRTR funds. ETROTLE aims to develop data-driven control systems using transfer learning and optimization methods to enhance the operation of wastewater treatment plants (WWTPs), focusing on environmental impact and sustainability. This repository contains the data used in the obtention of the transferability metrics, which entails the ANN models and simulations, pid parameters and scalers.