Machine Learning and Text Analysis in an Artificial Intelligent System for the Training of Air Traffic Controllers

Machine Learning and Text Analysis in an Artificial Intelligent System for the Training of Air Traffic Controllers

Tetiana Shmelova, Yuliya Sikirda, Nina Rizun, Vitaliy Lazorenko, Volodymyr Kharchenko
Copyright: © 2021 |Pages: 50
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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Background

Pilots and ATCs are working together for ensuring the safely, economically and efficiently flights of aircrafts (ACs). The pilots in crews are in communication with the ATC. ATCs are responsible for the order of movement of different types of ACs (manned and unmanned ACs, helicopters, etc. Control by the dispatcher includes absolutely all stages of the movement of the AC: from taxing it from the parking lot before take-off to taxiing to the parking lot after landing.

That is, in the Air Navigation System (ANS) operates the principle of “dual operator”: the pilot – the ATCs (Figure 1). Actual is the study of the regularities of the activities of both operators and their teams both in the process of fulfilling their professional duties and in social life. The authors present conceptual models of Decision Support Systems (DSS) and Expert Systems (ES) for human-operator (H-O) of ANS, such as ATCs, for training, in-flight emergencies, etc. The authors present Artificial Intelligence Technology and models of ES for H-O education in ANS.

Figure 1.

Air Navigation System operates the principle of “dual operator”

978-1-7998-5357-2.ch010.f01

The ANS is a complex purpose-oriented highly organized Human-Machine System (HMS) with a hierarchical structure of control of a stochastic system, with distinctive features which can be considered:

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