| Grant number: | 13/22416-4 |
| Support Opportunities: | Regular Research Grants |
| Start date: | May 01, 2014 |
| End date: | April 30, 2016 |
| Field of knowledge: | Engineering - Production Engineering - Operational Research |
| Principal Investigator: | Rodrigo Arnaldo Scarpel |
| Grantee: | Rodrigo Arnaldo Scarpel |
| Host Institution: | Divisão de Engenharia Mecânica (IEM). Instituto Tecnológico de Aeronáutica (ITA). Ministério da Defesa (Brasil). São José dos Campos , SP, Brazil |
Abstract
Data mining is defined as the automatic or semi-automatic process of extracting knowledge from databases for pattern, trend, association and dependency identification and is used in transforming crude data into useful knowledge to support the decision making process. Although the employed data mining methods are traditionally based on statistical methods, artificial intelligence and machine learning, such methods can be formulated as optimization problems. The goal of this project is to use data mining methods to identify temporal patterns on congestion delays for Brazilian airports. Air transport in Brazil has been recently liberalized and one of the consequences of this process was the concentration of flights in a few hubs. Although hubbing seems to benefit airlines and offers some advantages to travelers, the extent of excessive concentration at a hub can result in some negative economic impacts, namely, congestion delay which increases passenger's total travel time and airlines' operating costs. (AU)
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