PREDICTION OF AIRCRAFT FLIGHT DURATION

Weather is one of the most impacting sources of delay in terms of air traffic. Many applications have shown that the use of weather forecast enables the airport controllers to improve the efficiency and the safety of an airport. To date, it is still challenging to analyse a set of weather factors to predict the airport's capacity or the travel time of single aircraft. Mostly, this is due to the high complexity of the data. In this paper the results of an application that visualises complex weather data and its impact on air traffic are shown. Support Vector Regression (SVR) is then applied to demonstrate the prediction of aircraft flight duration by means of a modern nonlinear statistical technique.