The Variable Air Volume (VAV) system is considered to be a promising air conditioning scheme in most of the heating, ventilation and air conditioning (HVAC) applications. It is designed to deliver variable airflow rate for varying thermal load conditions prevailing inside the conditioned space. This paper reports the application of artificial neural network to optimize the fan speed in a variable air volume system. Based on the polynomial model, for various supply voltage and airflow rate the fan performance curves were obtained. These curves show a deviation from the real curves. Experimental results were utilized for training the artificial neural network (ANN) model. The optimized ANN model curves show less deviation with that of the real curves. This optimization technique can be used to predict the thermal comfort to be maintained in the conditioned space. © 2017 Elsevier B.V., All rights reserved.