Identification of entrant’s abilities on the basis of Sugeno-type fuzzy inference systems

    Svitlana Terenchuk   Affiliation
    ; Yuliia Riabchun Affiliation
    ; Maksym Delembovskyi   Affiliation


In the conditions of effective training in aviation for dispatchers and pilots, it requires the use of infocommunication systems capable of working under conditions of fuzzy uncertainty in real time. The functioning of such systems is based on fuzzy inference systems. However, the development and implementation of these systems requires the creation of fuzzy knowledge bases. Therefore, special attention in this study is paid to the creation of a system of fuzzy inferences and the formation of a fuzzy knowledge base of this system. The result is a lozenge-type fuzzy inference system. The fuzzy knowledge base of the system contains the rules according to which, based on the results of test computer game problems of varying complexity, a conclusion is formed about the applicant’s ability to acquire knowledge and skills in a certain specialty.When developing the rules, both the results of passing different levels of professionally oriented computer test games were taken into account, and the interest of dispatchers and pilots was taken into account. Therefore, the proposed fuzzy rules of the knowledge base of the fuzzy inference system make it possible to assess not only the ability of the controller or pilot to solve certain problems. This dependence of the input dataset on time allows the implementation of a fuzzy inference system of the Sugeno type, using clear input data in the formation of inferences.

Keyword : pilots, dispatchers, membership function plot, priory knowledgebase, fuzzy rule

How to Cite
Terenchuk, S., Riabchun, Y., & Delembovskyi, M. (2022). Identification of entrant’s abilities on the basis of Sugeno-type fuzzy inference systems. Aviation, 26(4), 176–182.
Published in Issue
Nov 18, 2022
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