Short-term electric load forecasting using computational intelligence methods

Accurate time series forecasting is a key issue to support individual and organizational decision making. In this paper, we introduce several methods for short-term electric load forecasting. All the presented methods stem from computational intelligence techniques: Random Forest, Nonlinear Autoregr...

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Detalhes bibliográficos
Autor principal: Jurado, Sergio (author)
Outros Autores: Peralta, J. (author), Nebot, Àngela (author), Mugica, Francisco (author), Cortez, Paulo (author)
Formato: conferencePaper
Idioma:eng
Publicado em: 2013
Assuntos:
Artificial neural networks
Evolutionary computation
Support vector machines
Random forest
Time series
Forecast
Ciências Naturais::Ciências da Computação e da Informação
Science & Technology
Texto completo:http://hdl.handle.net/1822/31409
País:Portugal
Oai:oai:repositorium.sdum.uminho.pt:1822/31409

Texto Completo

http://hdl.handle.net/1822/31409

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