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Aplicação do modelo de séries temporais para previsão do número de passageiros de uma companhia aérea

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  • da Silva Filho, Flávio Lopes

Abstract

O presente trabalho utiliza um modelo de séries temporais para realizar uma análise preditiva para prever resultados futuros com base em valores passados. Dessa forma, prevendo a quantidade de passageiros, que uma companhia aérea terá, nos próximos 6 meses. As previsões são feitas através de um modelo autorregressivo integrado de médias móveis sazonais, no inglês Seasonal Autoregressive Integrated Moving Average (SARIMA). Uma vez que a série temporal estudada tem tendência e sazonalidade o que classifica ela como não estacionária.

Suggested Citation

  • da Silva Filho, Flávio Lopes, 2022. "Aplicação do modelo de séries temporais para previsão do número de passageiros de uma companhia aérea," SocArXiv gmyaj, Center for Open Science.
    • Handle: RePEc:osf:socarx:gmyaj
    DOI: 10.31219/osf.io/gmyaj
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    References listed on IDEAS

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    1. Sun, Shaolong & Lu, Hongxu & Tsui, Kwok-Leung & Wang, Shouyang, 2019. "Nonlinear vector auto-regression neural network for forecasting air passenger flow," Journal of Air Transport Management, Elsevier, vol. 78(C), pages 54-62.
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