Інформаційні системи та технології
- ДокументIdentification 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, DaoudThe 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.
- ДокументIntelligent information technologies implementation to the process of professional self-identification(CEUR Workshop Proceedings, 2012-03) Aznaurian, Iryna; Yeremenko, Bohdan; Riabchun, Yuliia; Ploskiy, Vitalii; Mezzane, Daoud; Kryvinska, NataliaThe latest learning technologies implementation, based on new approaches to the presentation and acquisition of knowledge, requires appropriate modern methods of assessment. The search for perfect methods for assessing the abilities of entrants and students at the present stage of information technology development is extremely important, because the objectification of the assessment process, providing feedback, provides an opportunity to coordinate the development of personality. The main attention in this paper is directed on the decision of questions of professional orientation by means of testing which assumes performance of game tasks of a professional direction. The research presents a conceptual model of a specialized intelligent system, which is designed to support the decision of the applicant to choose a specialty of higher education institution of construction profile. The paper also shows fragments of the system with professional game tasks, which reflect the level of spatial imagination of the individual and the ability to perform functional duties in accordance with the personnel requirements of different professions of construction. The formation scheme of the recommendatory conclusion on results of performance of these tasks is offered the mechanism of fuzzy inference of the recommendatory conclusion is shown. Clear and fuzzy criteria are proposed that can be used to justify the recommendation conclusion. The possibility of using the fuzzy artificial neural network Takagi-Sugeno-Kang to setup the parameters of the model used to reflect certain professional abilities of the individual is shown.