With reference to the heat exchanger data: -ftp://ftp.esat.kuleuven.be/pub/SISTA/data/process_industry/exchanger.dat.gz -ftp://ftp.esat.kuleuven.be/pub/SISTA/data/process_industry/exchanger.txt (see also the process description in the cited paper)
Performed a nonlinear model identification using both the FROE method with polynomial NARX models and feedforward neural networks. Dataset divided in identification (first 3000 data) and validation data (the remaining 1000 data). Result compared with different model complexity assumptions.
Report available here
References: S. Bittanti and L. Piroddi, “Nonlinear identification and control of a heat exchanger: a neural network approach”, Journal of the Franklin Institute, vol. 334B, pp. 135–153, 1997.