IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 6 A Hierarchical Neural Model in Short-Term Load Forecasting Como, Italy July 24-July 27 ISBN: 0-7695-0619-4
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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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