Issue |
E3S Web Conf.
Volume 486, 2024
IX International Conference on Advanced Agritechnologies, Environmental Engineering and Sustainable Development (AGRITECH-IX 2023)
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Article Number | 03020 | |
Number of page(s) | 10 | |
Section | Information Technologies, Automation Engineering and Digitization of Agriculture | |
DOI | https://doi.org/10.1051/e3sconf/202448603020 | |
Published online | 07 February 2024 |
Modeling optimization problems when training engineering specialists using intelligent training systems
1 Department of Automated Control Systems for Biotechnological Processes, Russian Biotechnological University, 125080 Volokolamskoe highway, 11, Moscow, Russia
2 Department of Information Systems and Digital Technologies, Moscow State University of Technology and Management named after K.G. Razumovsky (First Cossack University), 109004 Zemlyanoy Val st., 73, Moscow, Russia
3 Department of Informatics and Computer Engineering of Food Production, Russian Biotechnological University, 125080 Volokolamskoe highway, 11, Moscow, Russia
* Corresponding author: i.s.polevshchikov@mail.ru
The article is devoted to the development of computer training tools for engineering specialists in the food industry. A method has been developed for modeling optimization problems for exercises in an intelligent training complex when training engineering specialists. The method differs from the known ones in many parameters that determine the properties of the optimization problems being studied for simulating these problems in the virtual environment. A method has been developed for modeling the complexity levels of exercises in intelligent training complex based on the parameters of optimization problems for adaptive training of specialists. The method differs from the known ones by using a dynamic set of parameters that determine the complexity of the structure of the optimization problem in the exercise, the complexity of the process of performing the exercise based on the properties of the simulated problem. The obtained research results in a practical aspect make it possible to create universal intelligent training complex for modeling optimization problems by production processes, considering the specifics of these tasks, instead of creating a new training complex for each topic or discipline being studied, which helps reduce the labor intensity of creating training courses for training specialists.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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