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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Veröffentlicht in:	Energies (Basel) Jg. 11; H. 7; S. 1636
Hauptverfasser:	Bouktif, Salah, Fiaz, Ali, Ouni, Ali, Serhani, Mohamed
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 2018
Schlagworte:	Artificial intelligence deep neural networks feature selection genetic algorithm Genetic algorithms long short term memory networks machine learning Neural networks short- and medium-term load forecasting Time series
ISSN:	1996-1073, 1996-1073
Online-Zugang:	Volltext
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