Air Traffic Forecasting Using Time Series Models: New Perspectives

Air Traffic Forecasting Using Time Series Models: New Perspectives

In this chapter, 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.

Author(s) Details

Manohar Dingari
Department of Mathematics, GITAM University, Hyderabad-502329, India.

Dr. D. Mallikarjuna Reddy
Department of Mathematics, GITAM University, Hyderabad-502329, India.

V. Sumalatha
Department of Statistics, Osmania University, Hyderabad-500007, India.

View Book :- http://bp.bookpi.org/index.php/bpi/catalog/book/180

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