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Aircraft Conflict Prediction using Machine Learning
The project entails exploring the use of Machine Learning (ML) techniques to assist in the training of air traffic controllers. The core goal is to train models that help predict if an instruction given by an air traffic controller may put an aircraft at risk of colliding with another aircraft during landing procedures.
Faculty Supervisor:
Diego Elias Damasceno Costa
Student:
Partner:
Adacel
Discipline:
Computer science
Sector:
Professional, scientific and technical services
University:
Concordia University
Program:
Accelerate
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