Predicting System loads with Artificial Neural Networks : Method and Result from "the Great Energy Predictor Shootout"

Summary, in Swedish

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.