AIRLINE ACTIVITY FORECASTING BY REGRESSION MODELS

Authors

  • Н. Білак National Aviation University
  • Н. Лукашенко National Aviation University
  • Ю. Якуба National Aviation University

DOI:

https://doi.org/10.18372/2306-1472.50.110

Keywords:

airline activity, correlation coefficient, Fisher criterion, forecast methods, linear and nonlinear regression models, mean error of model, seasonality index, trend equation

Abstract

Proposed linear and nonlinear regression models, which take into account the equation of trend and seasonality indices for the analysis and restore the volume of passenger traffic over the past period of time and its prediction for future years, as well as the algorithm of formation of these models based on statistical analysis over the years. The desired model is the first step for the synthesis of more complex models, which will enable forecasting of passenger (income level airline) with the highest accuracy and time urgency.

References

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Published

17-04-2012

How to Cite

Білак, Н., Лукашенко, Н., & Якуба, Ю. (2012). AIRLINE ACTIVITY FORECASTING BY REGRESSION MODELS. Advances in Aerospace Technology, 50(1), 40–45. https://doi.org/10.18372/2306-1472.50.110

Issue

Section

AEROSPACE SYSTEMS FOR MONITORING AND CONTROL