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Performance evaluation of forecasting models based on time series and machine learning techniques: an application to light fuel consumption in Brazil

Lucas Rodrigues, Luciano Rodrigues, Mirian Rumenos Piedade Bacchi

International Journal of Energy Sector Management (2022) 16 (4): 636–658.

https://doi.org/10.1108/IJESM-02-2021-0009

Published: 30 August 2021

..., 2021). The second, in its turn, refers to the average price of light fuels to the final consumer (ANP-National Agency of Petroleum, Natural Gas and Biofuels, 2021a). SARIMA model (p, d, q)(P, D, Q) (SAR) aims at explaining a stationary time series through...

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Forecasting the wind direction by using time series models with long-term memory (case study: Nayer region)

Paria Soleimani, Bahareh Emami, Meysam Rafei, Hooman Shahrasbi

International Journal of Energy Sector Management (2021) 15 (2): 385–396.

https://doi.org/10.1108/IJESM-04-2019-0002

Published: 15 July 2020

.... Design/methodology/approach Time series forecasting methods with long-term memory in this research have been used. Findings Eventually, the autoregressive fractionally integrated moving average (3,0,0)-FIGARCH (1,0,1) long-term memory model has more acceptable performance. The obtained error...

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Performance evaluation of forecasting models based on time series and machine learning techniques: an application to light fuel consumption in Brazil

Forecasting the wind direction by using time series models with long-term memory (case study: Nayer region)

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Performance evaluation of forecasting models based on time series and machine learning techniques: an application to light fuel consumption in Brazil

Forecasting the wind direction by using time series models with long-term memory (case study: Nayer region)

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