Non-linear HVAC computations using least square support vector machines

• DOI: 10.1016/j.enconman.2009.03.009
• Publication Date: 2009-04-09T04:32:49Z
• Authors: Mahendra Kumar; I.N. Kar
• Keywords: Robustness; Psychrometrics; Square (algebra)

This paper aims to demonstrate application of least square support vector machines (LS-SVM) to model two complex heating, ventilating and air-conditioning (HVAC) relationships. The two applications considered are the estimation of the predicted mean vote (PMV) for thermal comfort and the generation of psychrometric chart. LS-SVM has the potential for quick, exact representations and also possesses a structure that facilitates hardware implementation. The results show very good agreement between function values computed from conventional model and LS-SVM model in real time. The robustness of LS-SVM models against input noises has also been analyzed.