Mattias Ohlsson
Professor
Predicting System loads with Artificial Neural Networks : Method and Result from "the Great Energy Predictor Shootout"
Författare
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.
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.
Avdelning/ar
- Beräkningsbiologi och biologisk fysik - Har omorganiserats
Publiceringsår
1994
Språk
Svenska
Sidor
1063-1074
Publikation/Tidskrift/Serie
1994 Annual Proceedings of the American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc.
Dokumenttyp
Konferensbidrag
Förlag
ASHRAE
Ämne
- Computational Mathematics
Status
Published