Machine learning applied in the evaluation of airport projects in Brazil based on BIM models

Machine learning applied in the evaluation of airport projects in Brazil based on BIM models

Santos, Ítalo; Andrade, Max; Zanchettin, Cleber; Rolim, Adriana

Full Article:

In a country with continental dimensions like Brazil, air transport plays a strategic role in the development of the country. In recent years, initiatives have been promoted to boost the development of air transport, among which the BIM BR strategy stands out, instituted by decree nº9.983 (2019), decree nº10.306 (2020) and more recently, the publication of the airport design manual (SAC, 2021). In this context, this work presents partial results of a doctoral research based on the Design Science Research (DSR) method for the application of Machine Learning (ML) techniques in the Artificial Intelligence (AI) subarea, aiming to support SAC airport project analysts in the phase of project evaluation. Based on a set of training and test data corresponding to airport projects, two ML algorithms were trained. Preliminary results indicate that the use of ML algorithms enables a new scenario to be explored by teams of airport design analysts in Brazil.

In a country with continental dimensions like Brazil, air transport plays a strategic role in the development of the country. In recent years, initiatives have been promoted to boost the development of air transport, among which the BIM BR strategy stands out, instituted by decree nº9.983 (2019), decree nº10.306 (2020) and more recently, the publication of the airport design manual (SAC, 2021). In this context, this work presents partial results of a doctoral research based on the Design Science Research (DSR) method for the application of Machine Learning (ML) techniques in the Artificial Intelligence (AI) subarea, aiming to support SAC airport project analysts in the phase of project evaluation. Based on a set of training and test data corresponding to airport projects, two ML algorithms were trained. Preliminary results indicate that the use of ML algorithms enables a new scenario to be explored by teams of airport design analysts in Brazil.

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DOI: 10.5151/sigradi2023-234

Referências bibliográficas

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Como citar:

Santos, Ítalo; Andrade, Max; Zanchettin, Cleber; Rolim, Adriana; "Machine learning applied in the evaluation of airport projects in Brazil based on BIM models", p-869-881. In: . São Paulo: Blucher, 2024.
ISSN 23186968, DOI 10.5151/sigradi2023-234