The introduction of intellectual system for evaluating professional abilities of applicants into the activities of educational institutions

Abstract

The object of research is the methods and means of professional identification of applicants. The research aims to provide applicants with scientifically based decision support for choosing a field of study. The introduction of intelligent decision support systems in the process of self-actualization of applicants will significantly improve the effectiveness of vocational guidance activities of educational institutions. One of the biggest problems of the intellectualization of systems for assessing abilities and achievements is that the test results of applicants represent a lot of fuzzy data. At the same time, the correctness of data separation significantly depends on the construction of a fuzzy set of features for the conclusion of a diagnostic solution. In addition, the most common tests do not take into account the requirements for specialists of the construction industry. The basis of the developed system is tests to determine the personality structure of the Integrated Professional Orientation Diagnostics “Applicant”. This system contains reference information about the vocational category of training and tests for determining the structure of the individual. Conclusions are based on techniques that allow to predict the success of activities in various industries. The ability of a person to a certain professional activity reflects the ability to acquire special knowledge and skills in the learning process. That is why in the course of the study the Applicant tests were used. To improve the reliability of assessing the professional abilities of the applicant, it is proposed to use an intelligent system based on the Takagi-Sugeno-Kang fuzzy neural network. This choice is due to the fact that the Takagi-Sugeno-Kang network has a number of features that provide it with advantages in solving the problem of matching the abilities of an applicant to the possibility of acquiring knowledge and skills in a particular specialty. In particular, the ability of fuzzy neural networks to separate linearly inseparable data. This ensures the ability of the system to isolate the natural abilities of applicants from a mixture of data. Compared to other means, the Takagi-Sugeno-Kang network makes it possible to solve the problem of classifying a very large amount of data by a network of smaller dimension.