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Machine Learning and Text Analysis in an Artificial Intelligent System for the Training of Air Traffic Controllers
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Author(s): Tetiana Shmelova (National Aviation University, Ukraine), Yuliya Sikirda (Kirovograd Flight Academy of the National Aviation University, Ukraine), Nina Rizun (Gdansk University of Technology, Poland), Vitaliy Lazorenko (National Aviation University, Ukraine)and Volodymyr Kharchenko (National Aviation University, Ukraine)
Copyright: 2021
Pages: 50
Source title:
Research Anthology on Reliability and Safety in Aviation Systems, Spacecraft, and Air Transport
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-7998-5357-2.ch010
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Abstract
This chapter presents the application of new information technology in education for the training of air traffic controllers (ATCs). Machine learning, multi-criteria decision analysis, and text analysis as the methods of artificial intelligence for ATCs training have been described. The authors have made an analysis of the International Civil Aviation Organization documents for modern principles of ATCs education. The prototype of the neural network for evaluating the timeliness and correctness of the decision making by ATCs has been developed. The new theoretical and practical tasks for simulation and pre-simulation training have been obtained using expert judgment method. The methodology for sentiment analyzing the airline customers' opinions has been proposed. In addition, the examples of artificial intelligence systems and expert systems by the authors, students and colleagues from National Aviation University, Ukraine and Gdansk University of Technology, Poland have been proposed.
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