Non-linear HVAC computations using least square support vector machines

• Published in: Energy conversion and management Vol. 50; no. 6; pp. 1411 - 1418
• Main Authors: Kumar, Mahendra, Kar, I.N.
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01-06-2009; Elsevier
• Subjects: Air conditioning. Ventilation; Applied sciences; Energy; Energy. Thermal use of fuels; Exact sciences and technology; Heating, air conditioning and ventilation; HVAC; Least square support vector machines; Prediction model; Psychrometric chart; Techniques, equipment. Control. Metering; Thermal comfort; HVAC; Thermal comfort; Psychrometric chart; Least square support vector machines; Prediction model; Air conditioning; Prediction; Support vector machine; Modeling; Heating; Least squares method; Ventilation; Performance
• ISSN: 0196-8904; 1879-2227
• DOI: 10.1016/j.enconman.2009.03.009

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.