loading...
A Hierarchical Neural Model in Short-Term Load Forecasting
Como, Italy July 24-July 27
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.859403IEEE-INNS-ENNS International Joint Co ...
 This Article 
 
PDF
HTML
 
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Otávio A. S. Carpinteiro, Escola Federal de Engenharia de Itajub?
Alexandre P. A. da Silva, Escola Federal de Engenharia de Itajub?
Carlos H.L. Feichas, Escola Federal de Engenharia de Itajub?
This paper proposes a novel neural model to the problem of short-term load forecasting. The neural model is made up of two self-organizing map nets - one on top of the other. It has been successfully applied to domains in which the context information given by former events plays a primary role. The model was trained and assessed on load data extracted from a Brazilian electric utility. It was required to predict once every hour the electric load during the next 24 hours. The paper presents the results, and evaluates them.
Citation:
Otávio A. S. Carpinteiro, Alexandre P. A. da Silva, Carlos H.L. Feichas, "A Hierarchical Neural Model in Short-Term Load Forecasting," ijcnn, vol. 6, pp.6241, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 6, 2000
Usage of this product signifies your acceptance of the Terms of Use.