The proposed model could enable executives and managers in
charge of budget planning to accurately estimate the annual energy
consumption and determine the AECB in educational facilities. It
could be also applied to other types of resources (e.g., water consumption
or gas consumption) in educational facilities. Furthermore,
other methods, such as support vector machines or casebased
reasoning, could be used in future studies to develop a
hybrid model to improve prediction accuracy.