Automated evaluation models and algorithms for optimizing exercise assessments in food production training complexes

Abstract

The article is devoted to the development of models and algorithms of intelligent training complexes for training engineering specialists in the food industry. A method has been developed for comprehensive assessment of the quality of performing exercises on optimization problems in virtual environment. The method differs from the known ones in many parameters that determine the structure and specificity of these problems. It is formalized based on of fuzzy sets that describe incomplete knowledge when comparing the mathematical model of the problem created by the student with the reference one. The use of intelligent training complexes, in the software of which the presented method is implemented, will allow for ongoing monitoring and self-monitoring of students’ knowledge and skills when studying disciplines in the field of developing software for automated control systems for production processes. The use of intelligent training complexes ensures the collection and analysis of data on the dynamics in the formation of professional knowledge and skills among students in the development of mathematical software for automated control systems. Accordingly, the time for conducting control activities for the teacher is reduced, and the accuracy of the results of monitoring the formation of knowledge and skills among students is increased.