Žilinská univerzita v Žiline

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    Forecasting flight delays using machine learning
    (University of Žilina, 2024) Soloviov, Mykhailo; Badánik, Benedikt
    This article considers machine learning and its utilization in the domain of air transportation. The first part of this research aims to define machine learning, describe its historical development and helps delineate machine learning in a broader framework of other data analysis approaches such as artificial intelligence, deep learning and data science. In the second part, the research is meant to explain what machine learning is, tell more about the types of machine learning and how it is used in different scenarios in the aviation industry. This part of the thesis discusses certain areas and real examples of how machine learning is used by multiple companies (aircraft manufacturers) as well as examines the available conclusions of researches already undertaken in the area and determines their connection to the current one. Finally, the practical part of the thesis uses the collected real-time data about departures from two American airports, analyses it with the help of statistical Python-based tools, describes the developed machine-learning algorithm to predict delays, runs experiments on data and discusses results.
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    Umelá inteligencia, strojové učenie a trh práce
    (University of Zilina, 2020) Štalmachová, Katarína; Strenitzerová, Mariana
    Machine learning is becoming a key problem-solving in finance, industry or energy sectors. Human resource management is no exception; machine learning in this area allows progress to be made in streamlining functions. The aim of the article is to evaluate the possibilities of using machine learning in human resource management and the impacts of artificial intelligence on the labour market.
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    Use of artificial intelligence in unmanned aerial vehlice industry
    (University of Zilina, 2021) Buday, Adam; Ažaltovič, Viliam
    The aim of this paper is the analysis of the contemporary state of implementation of artificial intelligence in the area of unmanned aerial vehicles (UAV), and a proposal of further use of artificial intelligence systems in this area in the future. We analyse three essential areas in which artificial intelligence systems are currently being implemented to some extend – path following, object detection and tracking, and anti—collision systems. In each mentioned area we apply different solution methods, technical requirements, but also advantages and disadvantages of those solutions. We present an overview of artificial intelligence as a scientific branch. Finally, we present an overview of how artificial intelligence in the field of UAV could be implemented in the future, based on an analysis of the current state and direction of research and development in the present. We describe the possibilities of use artificial intelligence systems in two areas that are currently receiving the most attention at concept level, namely the flight of autonomous UAV swarms and the improvement of communication and data exchange between individual UAVs using artificial intelligence.