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

Mattias Ohlsson, Carsten Peterson, Hong Pi, Thorsteinn Rögnvaldsson, Bo Söderberg

Forskningsoutput: Kapitel i bok/rapport/Conference proceedingKonferenspaper i proceeding

Sammanfattning

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.
Originalspråksvenska
Titel på värdpublikation1994 Annual Proceedings of the American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc.
FörlagASHRAE
Sidor1063-1074
Antal sidor12
StatusPublished - 1994

Ämnesklassifikation (UKÄ)

  • Beräkningsmatematik

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