Time-series forecasting models

An application for climatological parameters in the city of Belém, Pará, Brazil

Authors

  • Douglas Matheus das Neves Santos Amazonia Federal Rural University (UFRA) https://orcid.org/0000-0002-5217-784X
  • Yuri Antônio da Silva Rocha Amazonia Federal Rural University (UFRA)
  • Danúbia Leão de Freitas Amazonia Federal Rural University (UFRA)
  • Paulo Roberto Estumano Beltrão Júnior Amazonia Federal Rural University (UFRA) https://orcid.org/0000-0002-4905-9738
  • Paulo Cerqueira dos Santos Junior Amazonia Federal Rural University (UFRA) https://orcid.org/0000-0002-6310-5040
  • Glauber Tadaiesky Marques Amazonia Federal Rural University (UFRA)
  • Otavio Andre Chase Amazonia Federal Rural University (UFRA)
  • Pedro Silvestre da Silva Campos Amazonia Federal Rural University (UFRA) https://orcid.org/0000-0001-8476-5569

DOI:

https://doi.org/10.31686/ijier.vol9.iss8.3239

Keywords:

Time Series, Forecasting, Meteorology, SARIMA, Holt-Winters

Abstract

Statistical and mathematical models of forecasting are of paramount importance for the understanding and study of databases, especially when applied to data of climatological variables, which enables the atmospheric study of a city or region, enabling greater management of the anthropic activities and actions that suffer the direct or indirect influence of meteorological parameters, such as precipitation and temperature. Therefore, this article aimed to analyze the behavior of monthly time series of Average Minimum Temperature, Average Maximum Temperature, Average Compensated Temperature, and Total Precipitation in Belém (Pará, Brazil) on data provided by INMET, for the production and application forecasting models. A 30-year time series was considered for the four variables, from January 1990 to December 2020. The Box and Jenkins methodology was used to determine the statistical models, and during their applications, models of the SARIMA and Holt-Winters class were estimated. For the selection of the models, analyzes of the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Autocorrelation Correlogram (ACF), and Partial Autocorrelation (PACF) and tests such as Ljung-Box and Shapiro-Wilk were performed, in addition to Mean Square Error (NDE) and Absolute Percent Error Mean (MPAE) to find the best accuracy in the predictions. It was possible to find three SARIMA models: (0,1,2) (1,1,0) [12], (1,1,1) (0,0,1) [12], (0,1,2) (1,1,0) [12]; and a Holt-Winters model with additive seasonality. Thus, we found forecasts close to the real data for the four-time series worked from the SARIMA and Holt-Winters models, which indicates the feasibility of its applicability in the study of weather forecasting in the city of Belém. However, it is necessary to apply other possible statistical models, which may present more accurate forecasts.

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Author Biographies

Douglas Matheus das Neves Santos, Amazonia Federal Rural University (UFRA)

Graduating in Environmental Engineering and Renewable Energies at the Federal Rural University of the Amazon - UFRA, campus Belém, Pará, Brazil

Yuri Antônio da Silva Rocha, Amazonia Federal Rural University (UFRA)

Graduating in Environmental Engineering and Renewable Energies at the Federal Rural University of the Amazon - UFRA, campus Belém, Pará, Brazil

Danúbia Leão de Freitas, Amazonia Federal Rural University (UFRA)

Graduating in Environmental Engineering and Renewable Energies at the Federal Rural University of the Amazon - UFRA, campus Belém, Pará, Brazil.

Paulo Roberto Estumano Beltrão Júnior, Amazonia Federal Rural University (UFRA)

Graduating in Environmental Engineering and Renewable Energies at the Federal Rural University of the Amazon - UFRA, campus Belém, Pará, Brazil.

Paulo Cerqueira dos Santos Junior, Amazonia Federal Rural University (UFRA)

PhD in Statistics, and professor at the Federal Rural University of the Amazon - UFRA, Belém campus, Pará Brazil, Ciberespacial Institute – ICIBE.

Glauber Tadaiesky Marques, Amazonia Federal Rural University (UFRA)

PhD in Physics, and professor at the Federal Rural University of the Amazon - UFRA, Belém campus, Pará Brazil, Ciberespacial Institute – ICIBE.

Otavio Andre Chase, Amazonia Federal Rural University (UFRA)

PhD in Electrical Engineering, IEEE Senior Member, and professor at the Federal Rural University of the Amazon - UFRA, Belém campus, Pará Brazil, Ciberespacial Institute – ICIBE.

Pedro Silvestre da Silva Campos, Amazonia Federal Rural University (UFRA)

PhD in Agricultural Sciences, and professor at the Federal Rural University of the Amazon - UFRA, Belém campus, Pará Brazil, Ciberespacial Institute – ICIBE.

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Published

01-08-2021

How to Cite

Santos, D. M. das N., Y. A. da S. Rocha, D. Freitas, P. Beltrão, P. . Santos Junior, G. Marques, O. Chase, and P. Campos. “Time-Series Forecasting Models: An Application for Climatological Parameters in the City of Belém, Pará, Brazil”. International Journal for Innovation Education and Research, vol. 9, no. 8, Aug. 2021, pp. 24-47, doi:10.31686/ijier.vol9.iss8.3239.
Received 2021-06-10
Accepted 2021-06-29
Published 2021-08-01

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