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

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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Bibliographic Details
Main Authors: Salah Bouktif, Ali Fiaz, Ali Ouni, Mohamed Adel Serhani
Format: Article
Language:English
Published: MDPI AG 2018-06-01
Series:Energies
Subjects:
deep neural networks
long short term memory networks
short- and medium-term load forecasting
machine learning
feature selection
genetic algorithm
Online Access:http://www.mdpi.com/1996-1073/11/7/1636

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http://www.mdpi.com/1996-1073/11/7/1636

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