Mattias Ohlsson, Carsten Petersson, Hong Pi, Thorstein Rögnvaldsson and Bo Söderberg
Predicting System Loads with Artificial Neural Networks - Method and Result from 'The Great Energy Predictor Shootout'
In Proceedings of American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. 100 , 1063-1074 (1994)

We devise a feed-forward Artificial Neural Network (ANN) procedure for predicting utility loads and present the resulting predictions for two test problems given by ``The Great Energy Predictor Shootout - The First Building Data Analysis and Prediction Competition''. Key ingredients in our approach are a method (delta-test) for determining relevant inputs and the Multilayer Perceptron. These methods are briefly reviewed together with comments on alternative schemes like fitting to polynomials and the use of recurrent networks.

LU TP 93-24