Forecasting models for the electricity consumption of the cement industry in Brazil
RF da Silva Mendes… - …, 2023 - ojs.observatoriolatinoamericano …
RF da Silva Mendes, K da Costa, FLC da Silva, JSC Coelho, CAR Vera-Tudela, RV Pinto
OBSERVATÓRIO DE LA ECONOMÍA LATINOAMERICANA, 2023•ojs.observatoriolatinoamericano …The consumption of electric energy in the Brazilian industrial sector has been investigated
over the past few years. This interest is related to sector development, energy planning, and
energy efficiency. Thus, forecasting models are important for decision-making. The objective
of this work is to compare different forecasting models applied to monthly data on electric
energy consumption in the cement industry in Brazil. Therefore, the Holt-Winters method, the
Seasonal ARIMA model, the dynamic linear model, and the autoregressive neural network …
over the past few years. This interest is related to sector development, energy planning, and
energy efficiency. Thus, forecasting models are important for decision-making. The objective
of this work is to compare different forecasting models applied to monthly data on electric
energy consumption in the cement industry in Brazil. Therefore, the Holt-Winters method, the
Seasonal ARIMA model, the dynamic linear model, and the autoregressive neural network …
Abstract
The consumption of electric energy in the Brazilian industrial sector has been investigated over the past few years. This interest is related to sector development, energy planning, and energy efficiency. Thus, forecasting models are important for decision-making. The objective of this work is to compare different forecasting models applied to monthly data on electric energy consumption in the cement industry in Brazil. Therefore, the Holt-Winters method, the Seasonal ARIMA model, the dynamic linear model, and the autoregressive neural network model were used. Through the considered accuracy metrics, the Seasonal ARIMA model showed the best predictive performance for the analyzed period.
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