MULTIPLE LINEAR REGRESSION MODEL OF AIRPORT AVIATION SECURITY.

Abstract

Airport security is always a high priority. It includes the control of passengers, luggage and vehicles to prevent possible threats. The relevance of these measures does not decrease due to constant changes in methods of threats and technologies for their prevention.

In the Convention on the International Organization of Civil Aviation (Appendix 19), the ICAO proposed "Management of Flight Safety" in which changes to the global approach to ANS are indicated. Implementation at the global, regional and state levels includes areas of responsibility of organizational structures, necessary procedures and political aspects.

One of the main problems of security analysis is the choice of the appropriate mathematical apparatus. Accordingly, the development and analysis of air safety data management is an important tool for increasing the level of control and decision-making regarding processes and procedures, which will guarantee positive results when making the most effective management decisions.

A linear regression model can be useful for analyzing some aspects of aviation security at airports. For example, it can be used to predict the prior probability of certain events based on certain factors. Using a linear regression model, the author substantiated the influence of factors (world aviation safety index, passenger traffic and tariffs) on the level of aviation safety at airports. However, safety in aviation is a complex issue that includes many aspects, therefore, to fully ensure safety, it may be necessary a combination of different models and approaches.