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An artificial neural network backpropagation model with three-phase annealing was used for the first building energy prediction competition held by the American Society of Heating, Refrigerating and Air-Conditioning Engineers in 1993. Three-phase annealing is an empirical method to gradually reduce the learning rate during the training period in order to improve accuracy in a relatively short time. The preprocessing of the competition data, methods of backpropagation training (including three-phase annealing), modelling guidelines for the network, and results of the prediction are presented and discussed.

KEYWORDS: artificial intelligence, expert systems, calculating, buildings, energy consumption, competition