Predicting system loads with artificial neural networks: Methods and results from ``The great energy predictor shootout``

A feed-forward artificial neural network (ANN) procedure has been devised for predicting utility loads; the resulting predictions are presented for two test problems given by ``The Great Energy Predictor Shootout-The First Building Data Analysis and Prediction Competition`` (Kreider and Haberl 1994). Key ingredients in this approach are the multilayer perceptron and a method ({delta}-test) for determining relevant inputs. These methods are briefly reviewed, together with comments on alternative schemes such as fitting to polynomials and the use of recurrent networks.