Analysis of flight delays in aviation system using different classification algorithms and feature selection methods

Abstract

Data mining is a process of finding correlations and collecting and analysing a huge amount of data in a database to discover patterns or relationships. Flight delay creates significant problems in the present aviation system. Data mining techniques are desired for analysing the performance in which micro-level causes propagate to make system-level patterns of delay. Analysing flight delays is very difficult – both when looking from a historical view as well as when estimating delays with forecast demand. This paper proposes using Decision Tree (DT), Support Vector Machine (SVM), Naive Bayesian (NB), K-nearest neighbour (KNN) and Artificial Neural Network (ANN) to study and analyse delays among aircrafts. The performance of different data mining methods is found in the different regions of the updated datasets on these classifiers. Finally, the result shows a significant variation in the performance of different data mining methods and feature selection for this problem. This paper aims to deal with how data mining techniques can be used to understand difficult aircraft system delays in aviation. Our aim is to develop a classification model for studying and reducing delay using different data mining methods and, in this manner, to show that DT has a greater classification accuracy. The different feature selectors are used in this study in order to reduce the number of initial attributes. Our results clearly demonstrate the value of DT for analysing and visualising how system-level effects happen from subsystem-level causes.

Analysis of Flight Disruption Data to Determine Problem Areas Utilizing Database Applications

“…Despite the complexities, certain patterns of flight delays are consistent with the airline's schedule performance. The case study yielded some interesting outcomes [8].…”

“…Security: Delays or cancellations caused by evacuation of a terminal or concourse, re-boarding of the aircraft because of a security breach, inoperative screening equipment and/or long lines more than 29 minutes at screening areas." [8]. Our research uses the Relational Database Management System to give flight delay statistical information to the end user via a website.…”

Analysis of Flight Disruption Data to Determine Problem Areas Utilizing Database Applications

“…Despite the complexities, certain patterns of flight delays are consistent with the airline's schedule performance. The case study yielded some interesting outcomes [6].…”

“…Security: Delays or cancellations caused by evacuation of a terminal or concourse, re-boarding of the aircraft because of a security breach, inoperative screening equipment and/or long lines more than 29 minutes at screening areas." [6].…”