Authors:
Hugo Alonso
1
and
António Loureiro
2
Affiliations:
1
Universidade de Aveiro and Universidade Lusófona do Porto, Portugal
;
2
Aeroporto do Porto, Portugal
Keyword(s):
Flight Delay Prediction, Ordinal Classification, Unimodal Model, Neural Networks, Trees.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computational Intelligence
;
Data Manipulation
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Methodologies and Methods
;
Neural Based Data Mining and Complex Information Processing
;
Neural Networks
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
;
Supervised and Unsupervised Learning
;
Theory and Methods
Abstract:
Managing an airport is very complex. Decisions are often based on common sense and influence several variables, such as flight delay. This paper considers the problem of predicting flight departure delay at Porto Airport. As far as we know, this the first study on the subject. The problem is treated as an ordinal classification task and a suitable approach, based on the so-called unimodal model, is used to predict the delay. The unimodal model is implemented using neural networks and, for comparison purposes, also using trees.