Human factor, also known as ergonomics, primarily focuses on interactions of people with their surroundings, tools, and technology. Human factor analysis helps humans to improve their safety and performance with reference to their involvement with the surroundings as well as tools and technologies they are operating. Human factors play a significant role in aviation safety management and help to minimize pilot errors. This research explores human factors with reference to Human Factors Analysis and Classification System (HFACS). The research also evaluates the inter-relationship between these factors and identifies the influence of these factors within each other. Finally, the research develops a framework for prediction of human factors under different categories using machine learning and artificial intelligence techniques. The research also provides directions for the future scope of research with reference to prediction of human factors using other techniques such as regression and clustering, to achieve better insights.


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    Titel :

    Predicting Aviation Safety Human Factors Using Artificial Intelligence and Machine Learning Classification


    Beteiligte:
    Khan, Abid Ali (Herausgeber:in) / Hossain, Mohammad Sayeed (Herausgeber:in) / Fotouhi, Mohammad (Herausgeber:in) / Steuwer, Axel (Herausgeber:in) / Khan, Anwar (Herausgeber:in) / Kurtulus, Dilek Funda (Herausgeber:in) / Udupi, Prakash Kumar (Autor:in) / Venugopal, Dhanalakshmi (Autor:in) / Pandey, Jitendra (Autor:in) / Dattana, Vishal (Autor:in)

    Kongress:

    International Conference on Aeronautical Sciences, Engineering and Technology ; 2023 ; Muscat, Oman October 03, 2023 - October 05, 2023



    Erscheinungsdatum :

    26.12.2023


    Format / Umfang :

    6 pages




    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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