Open AccessInformation technologies in the management of technical systems - development of the engineering education
Author(s) -
Elena E. Kotova,
Yu. А. Korablev,
Andrey S. Pisarev,
М. Yu. Shestopalov
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1864/1/012124
Subject(s) - computer science , process (computing) , context (archaeology) , engineering management , knowledge management , information system , field (mathematics) , automation , data management , information technology , control (management) , analytics , data science , engineering , artificial intelligence , data mining , mechanical engineering , paleontology , electrical engineering , mathematics , pure mathematics , biology , operating system
The current level of production development requires the training of qualified specialists capable of solving complex scientific and technical problems in the field of technical systems management using rapidly changing information technologies. Consequently, the training of professional personnel should provide for the needs of developers of advanced control systems for complex dynamic objects. This problem is successfully solved at the Department of Automation and Control Processes (ACP department) in ETU “LETI”. Students training is carried out in two complementary directions “Management in technical systems” and “Information systems and technologies”. Long-term experience proves the advisability of choosing such an approach in the context of rapidly developing technologies. The report contains studies based on the application of data analysis methods and models that dynamically integrate the information necessary for adaptive management of the process of advanced specialists training. The dataset includes: actual employers’ data, production needs, on the one hand, data obtained during the educational process, on the other hand. At the same time, the data set includes data that enable students to assess the effectiveness of the educational services provision, the level of professional training in the areas of specialty. Comprehensive analysis of data integrated in a unified environment, based on the methods of intelligent systems, analytics and knowledge engineering, proves the validity of choosing this approach in the learning process.