Air Traffic Forecasting using Time Series Models

Abstract

In this paper, Holt-Winters’ Additive model is fitted to the data regarding Domestic Air traffic in Air India flights. The investigation was done using dataset on number of passengers travelling by Air India domestic flights during January 2012 to November 2018. To prepare a tool to analyze the traffic flow monthly wise this helps Air India to revise their services. ARIMA model also has been fitted to the data, and compared with Holt-Winters’ Additive model. Finally, the results, findings and analysis proved that the Holt-Winters’ Additive model is superior to the ARIMA model for this data. This kind of analysis is very useful for forecasting the Air traffic.