Інформаційні системи та технології

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  • Документ
    Identification of Entrant's Abilities on the Basis Fuzzy Inference Systems
    (ITTAP’2021, 2021-11) Terenchuk, Svitlana; Riabchun, Yuliia; Poltorachenko, Nataliia; Aznaurian, Iryna; Levashenko, Vitaly; Mezzane, Daoud
    The paper is devoted to solving such important social task as providing professional assistance to entrants at choosing a specialty for study. The relevance of the development and implementation intelligent infocommunication systems into the entrant's professional abilities assessing process is shown. The aim of the research is to create the Fuzzy Inference System, which is the unit of the Neuro-Fuzzy Inference System of the Specialized Intellectual System of Entrant's Abilities Identification. It is proposed the neuro-fuzzy inference system from pairs of fuzzy artificial neural networks of Takagi-Sugeno-Kanga categories and Sugeno-type fuzzy inference systems. The possibility of using fuzzy artificial neural networks of Takagi-Sugeno-Kanga categories to solve the problem of estimation the entrant's special abilities is rationaled. Also the expediency of using the fuzzy Sugeno-type inference system is rationaled and customizing up input data's membership functions is shown. Herewith the input variables reflect the expression measure of the entrant's interest in the profession and the results of passing computer game tasks' different levels. So, the created Sugeno-type fuzzy inference system, unlike the existing ones, is based on rules that reflect the interests and abilities of the person to the profession. Thus for formation of the personality portrait computer game tasks of professional orientation are used. Unified rules that form knowledgebase in fuzzy inference systems are based on the expert experience. At the same time the results of Fuzzy Inference System work confirm the system capability to solve the problem of the person professional identification in fuzzy conditions without of rules-analogues in the system's knowledgebase.