Optimal Deep Learning LSTM Model for Electric Load Forecasting using Feature Selection and Genetic Algorithm: Comparison with Machine Learning Approaches †

Background: With the development of smart grids, accurate electric load forecasting has become increasingly important as it can help power companies in better load scheduling and reduce excessive electricity production. However, developing and selecting accurate time series models is a challenging t...

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Auteurs principaux:	Salah Bouktif, Ali Fiaz, Ali Ouni, Mohamed Adel Serhani
Format:	Artigo
Langue:	Inglês
Publié:	MDPI AG 2018-06-01
Collection:	Energies
Sujets:	deep neural networks long short term memory networks short- and medium-term load forecasting machine learning feature selection genetic algorithm
Accès en ligne:	http://www.mdpi.com/1996-1073/11/7/1636
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