Formation of the Optimal Load of High School Students Using a Genetic Algorithm and a Neural Network

Applied Sciences

卷:11

Michael Viktorovich Smirnov¹  Aleksey Viktorovich Osipov¹  Elena Petrovna Dogadina¹  Stanislav Vadimovich Suvorov² 

[1] Department of Data Analysis and Machine Learning, Federal State Budgetary Institution of Higher Education, Financial University under the Government of the Russian Federation, 105187 Moscow, Russia;

[2] Federal State Autonomous Educational Institution of Higher Education, Moscow Polytechnic University, 107023 Moscow, Russia;

关键词: neural networks;    genetic algorithm;    queuing theory;    education;   

DOI  :  10.3390/app11115263

来源: DOAJ

【 摘 要 】

The problem of the effectiveness of teaching can be successfully solved only if the high quality of lessons is supported by well-organized homework of students. The question of homework occupies one of the main places in educational activities since this question is directly related to the health of the child. A competent approach to minimizing the time for completing homework, taking into account the maximum efficiency obtained from the learning process, can preserve the health of students to some extent. The article describes a method for obtaining the most comfortable results of the process of completing homework, which are a Pareto set. This method is implemented using a genetic algorithm and queuing theory, and the selection of homework is carried out on the basis of intellectual analysis of the text of tasks and is a scale of a certain range. The proposed algorithm successfully obtains the solutions of the Pareto set and minimizes the efforts of school students while achieving the maximum efficiency of the educational process to preserve their health. Compared with other known algorithms, the results obtained show that the proposed algorithm demonstrates fairly accurate optimization characteristics presented in the form of a Pareto set. Furthermore, combining a genetic algorithm, queuing theory apparatus, and a neural network makes it possible to model the studied subject area more accurately.

【 授权许可】

Unknown