TY - JOUR
TI - Modeling and identification of heat exchanger process using least squares support vector machines
AU - Al-Dhaifallah Mujahed
AU - Nisar Kottakkaran Sooppy
AU - Agarwal Praveen
AU - Elsayyad Alaa
JN - Thermal Science
PY - 2017
VL - 21
IS - 6
SP - 2859
EP - 2869
PT - Article
AB - In this paper, Hammerstein model and non-linear autoregressive with eXogeneous inputs (NARX) model are used to represent tubular heat exchanger. Both models have been identified using least squares support vector machines based algorithms. Both algorithms were able to model the heat exchanger system with-out requiring any a priori assumptions regarding its structure. The results indicate that the blackbox NARX model outperforms the NARX Hammerstein model in terms of accuracy and precision.