NL_Stat_Dyn_NN_Data

This repository contains the data used for training and validating the hybrid nonlinear static - nonlinear dynamic series and parallel neural network structures for three different nonlinear case study examples. For more details about the network architectures and training algorithms developed, please refer to the paper "Hybrid Series/Parallel All-Nonlinear Dynamic-Static Neural Networks: Development, Training, and Application to Chemical Processes" (Mukherjee, A., Bhattacharyya, D.) published in the journal 'Industrial and Engineering Chemistry Research' which can be accessed at https://pubs.acs.org/doi/10.1021/acs.iecr.2c03339.