Modeling and forecasting electricity consumption amid the COVID-19 pandemic: Machine learning vs. nonlinear econometric time series models

Modeling and forecasting electricity consumption amid the COVID-19 pandemic: Machine learning vs. nonlinear econometric time series models

Accurately modeling and forecasting electricity consumption remains a challenging task due to the large number of the statistical properties that characterize this time series such as seasonality, trend, sudden changes, slow decay of autocorrelation function, among many others. This study contribute...

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Bibliographic Details
Main Author: Lanouar, Charfeddine (author)
Other Authors: Zaidan, Esmat (author), Alban, Ahmad Qadeib (author), Bennasr, Hamdi (author), Abulibdeh, Ammar (author)
Format: article
Published: 2023
Subjects:
Electricity consumption
Forecasting
COVID-19
Nonlinear econometric models
Machine and deep learning models
Online Access:http://dx.doi.org/10.1016/j.scs.2023.104860
https://www.sciencedirect.com/science/article/pii/S2210670723004717
http://hdl.handle.net/10576/47967
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Internet

http://dx.doi.org/10.1016/j.scs.2023.104860
https://www.sciencedirect.com/science/article/pii/S2210670723004717
http://hdl.handle.net/10576/47967

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