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Salvi, Nikhil Sagarendra (2022) Critical Analysis on Flight Cancellations and Predictive Analysis on Flight Delays using Automated Machine Learning. Masters thesis, Dublin, National College of Ireland.
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Abstract
In the 21st century, every nation needs to grow in the global network and get connected to other countries, and for this purpose, the aviation industry plays a vital role. The aviation or airline industry is responsible for rapid transportation worldwide. This industry generates economic growth, cre- ates employment, and provides facilities. As the number of passengers and air traffic is increasing, the airline industries are adopting advanced technologies to make the processes to make the process quick and easy. But, with this, a tremendous amount of data gets generated. Industries are using this data to understand the business more and find out areas of improvement to provide the best services to their customers. This helps the industry to sustain itself in a competitive environment and grow its business. In this research project, a critical analysis of flight delay is done. Also, a predictive model is built using automated machine learning. This model has provided the best suitable algorithm to predict flight delays accurately so that the air- line industries strategize and prepare the airport management system.
| Item Type: | Thesis (Masters) |
|---|---|
| Supervisors: | Name Email Horn, Christian UNSPECIFIED |
| Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science H Social Sciences > HD Industries. Land use. Labor > Specific Industries > Aviation Industry Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning |
| Divisions: | School of Computing > Master of Science in Data Analytics |
| Depositing User: | Tamara Malone |
| Date Deposited: | 25 May 2023 14:56 |
| Last Modified: | 25 May 2023 14:56 |
| URI: | https://norma.ncirl.ie/id/eprint/6647 |
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