PREDICTIVE MODELING OF FLIGHT DELAYS USING DECISSION TREE

Abstract

Nowadays, although technology has developed on an unimaginable scale, there are still factors that can disrupt the safe and smooth functioning of many areas of daily life. One such factor are delays. Unquestionably, they are an undesirable and, in some cases, even dangerous element. A particular case in point may be air traffic, which is one of the most technologically advanced areas. However, air traffic delays, which occur quite frequently, have made it desirable to study this area based on airport capacity modelling and machine learning methods, with the main focus on decision tree algorithms. Based on these decision tree methods, the result of acquiring and processing data and variables has been the creation of specific models that can support air traffic management and, consequently, the levelling of the resulting delays.