Please use this identifier to cite or link to this item:
http://www.repositorio.ufop.br/jspui/handle/123456789/1189
Title: | A hierarchical hybrid neural model in short-termload forecasting. |
Authors: | Carpinteiro, Otávio Augusto Salgado Reis, Agnaldo José da Rocha Quintanilha Filho, Paulo Sergio |
Issue Date: | 2004 |
Citation: | CARPINTEIRO, O. A. S.; REIS, A. J. da R.; QUINTANILHA FILHO, P. S. A hierarchical hybrid neural model in short-termload forecasting. In: Simpósio Brasileiro de Redes Neurais, 2004. Natal. Anais... Natal: SBRN, 2004. p.1-6. Disponível em: <http://www.gpesc.unifei.edu.br/tmp/sbrn2004-3669.pdf>. Acesso em: 23 jul. 2012. |
Abstract: | This paper proposes a novel neural model to the problem of short-term load forecasting. The neural model is made up o f two self-organizing map nets one on top of the other |,and a single-layer perceptron. It has application into domains in which the context information given by former events plays aprimary role. The model was trained and assessed onload data extracted from a Brazilian electric utility. It was required to predict once every hour the electric load during the next six hours. The paper presents the results, and evaluates them. |
URI: | http://www.repositorio.ufop.br/handle/123456789/1189 |
metadata.dc.rights.license: | O Periódico Applied Soft Computing concede permissão para depósito do artigo no Repositório Institucional da UFOP. Número da licença: 3291280500461. |
Appears in Collections: | DECAT - Trabalhos apresentados em eventos |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
EVENTO_HierarchicalHybridNeural.pdf | 214,19 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.