A Novel Accurate and Fast Converging Deep Learning-Based Model for Electrical Energy Consumption Forecasting in a Smart Grid

A Novel Accurate and Fast Converging Deep Learning-Based Model for Electrical Energy Consumption Forecasting in a Smart Grid

Energy consumption forecasting is of prime importance for the restructured environment of energy management in the electricity market. Accurate energy consumption forecasting is essential for efficient energy management in the smart grid (SG); however, the energy consumption pattern is non-linear wi...

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Bibliographic Details
Main Authors: Ghulam Hafeez, Khurram Saleem Alimgeer, Zahid Wadud, Zeeshan Shafiq, Mohammad Usman Ali Khan, Imran Khan, Farrukh Aslam Khan, Abdelouahid Derhab
Format: Article
Language:English
Published: MDPI AG 2020-05-01
Series:Energies
Subjects:
smart grid
electric energy consumption forecasting
deep learning
factored conditional restricted Boltzmann machine
rectified linear unit
modified feature selection technique
Online Access:https://www.mdpi.com/1996-1073/13/9/2244

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https://www.mdpi.com/1996-1073/13/9/2244

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