An Approach of Applying Machine Learning Model in Flight Delay Prediction- A Comparative Analysis

Abstract

Flight delay is a major issue in the aviation industry. In commercial aviation, if a flight reaches its destination 15 minutes later than the scheduled arrival, it is said to be delayed. Flight delays cause a great deal of bother to travelers. It could make them late to their booked occasions or miss a corresponding flight, accordingly prompting outrage and dissatisfaction. Likewise, travelers may not generally be entitled for a refund when a postponement happens. Carriers report that couple of the numerous reasons prompting most flight delays are carrier glitches, climate conditions, support issues with the airplane and congestion in air traffic. Rapid development in airline industry has led to an increased number of aircrafts in the skies, this has brought about air-gridlock causing flight delays. Flight delays are not only extremely undesirable financially but also have adverse environmental effects. Air-traffic management is becoming increasingly challenging. The aim of our research work is to predict the delay of flights due to various factors using machine learning and deep learning so as to minimize losses and increase customer satisfaction. This Machine Learning model could be integrated with Airlines systems for the use of staff and customers and it could also rank Airlines and flights based on delays.