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...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2018-06-01
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Series: | Energies |
Subjects: | |
Online Access: | http://www.mdpi.com/1996-1073/11/7/1636 |