Development of a software product for forecasting the entrance of applicants to higher educational institutions

Keywords: neural networks, higher education, artificial intelligence, forecasting, enrollee

Abstract

The article highlights the problems of forecasting the entrance of university entrants into higher education institutions in connection with the constant fluctuations of the labor market and socio-demographic processes, which completely violate the results of the predictions of classical statistical methods, therefore the author studies the necessity of developing a software tool for forecasting the entrance of entrants to higher education institutions , which will operate on the basis of the neural network and will be able to adapt to the conditions of constant chaotic oscillations. The author emphasizes that neural networks are a modern and leading area of research and program development, and proves that the use of neural networks in the prediction of educational processes will allow obtaining results with a much higher level of accuracy and less time. The article contains analysis of theoretical information about neural networks and analysis of existing algorithms of neural networks operation. The author mentions the advantages and disadvantages of each algorithm, provides a comparative analysis and concludes that it is expedient to use each of the methods in a software tool for forecasting the entrance of entrants to higher education institutions. In the course of the work, the author carried out software modelling of the various methods of teaching neural networks, conducted testing, received and disclosed the results of each method, carried out an analysis of their actual effectiveness in predicting small and large volumes of information with different inputs and made the conclusion that the expediency of their use in the future software. The mathematical features of the construction of neural networks, their training and further use are revealed, the basic requirements for the future of the software product, namely the method of work, input data, the method of displaying the results and the layout of the future software, are revealed. The main blocks of the software for forecasting the entrance of entrants to higher education institutions are shown. It was concluded that it is expedient to use neural networks and work on a software tool for forecasting the entrance of entrants to higher educational institutions has been started, vectors of further researches and developments have been selected.

References

СПИСОК ВИКОРИСТАНИХ ДЖЕРЕЛ

Букреєв, Д. О. (2018). Прогнозування фондового ринку за допомогою нейронних мереж. Інформаційні технології в освіті та науці: збірник наукових праць, (10), 36-43.

Васенков, Д. В. (2007). Методы обучения искусственных нейронных сетей. Компьютерные инструменты в образовании, (1), 20-29.

Короткий, С. (1996a). Нейронные сети: обучение без учителя. GotAI.NET - Материалы - Нейронные сети. Взято с http://www.gotai.net/documents/doc-nn-004.aspx.

Короткий, С. (1996b). Нейронные сети: основные положения. GotAI.NET - Материалы - Нейронные сети. Взято с http://www.gotai.net/documents/doc-nn-002.aspx.

Короткий, С. (1996c). Нейронные сети Хопфилда и Хемминга. GotAI.NET - Материалы - Нейронные сети. Взято с http://www.gotai.net/documents/doc-nn-005.aspx.

Осадчий, В. В., & Осадча, К. П. (2015). Сучасні реалії і тенденції розвитку інформаційно-комунікаційних технологій в освіті. Інформаційні технології і засоби навчання, 4 (48), 47-57. Взято з https://journal.iitta.gov.ua/index.php/itlt/article/view/1252.

Нестеренко, О. В., Савенков, О. І., & Фаловський, О. О. (2016). Інтелектуальні системи підтримки прийняття рішень: навч. посібник. Київ, Україна: Національна академія управління.

Стариков, А. (2005). Генетические алгоритмы – математический аппарат. BaseGroup Labs. Взято с https://basegroup.ru/community/articles/ga-math.

Федосин, С. А., Ладяев, Д. А., & Марьина, О. А. (2010). Анализ и сравнение методов нейронных сетей. Вестник Мордовского университета. Серия «Физико-математические науки», (4), 79-88.

Шаров, С. В. (2015). Сучасний стан розвитку інтелектуальних інформаційних систем. Вісник Чернігівського національного педагогічного університету. Серія: Педагогічні науки, (130), 111-114.

Smith, L. (1996). An Introduction to Neural Networks. Retrieved from http://www.cs.stir.ac.uk/~lss/NNIntro/InvSlides.html.

REFERENCES (TRANSLATED AND TRANSLITERATED)

Bukreiev, D. O. (2018). Forecasting the stock market with the help of neural networks. Informatsiini tekhnolohii v osviti ta nautsi: zbirnyk naukovykh prats, (10), 36-43. (in Ukrainian)

Vasenkov, D. V. (2007). Methods of Teaching Neural Networks. Kompyuternyie instrumentyi v obrazovanii, (1), 20-29. (in Russian)

Korotkiy, S. (1996a). Neural Networks: Learning Without a Teacher. GotAI.NET – Materialyi – Neyronnyie seti. Retrieved on http://www.gotai.net/documents/doc-nn-004.aspx. (in Russian)

Korotkiy, S. (1996b). Neural Networks: Key Provisions. GotAI.NET – Materialyi – Neyronnyie seti. Retrieved from http://www.gotai.net/documents/doc-nn-002.aspx. (in Russian)

Korotkiy, S. (1996c). Hopfield and Hamming Neural Networks. GotAI.NET – Materialyi – Neyronnyie seti. Retrieved from http://www.gotai.net/documents/doc-nn-005.aspx. (in Russian)

Osadchyi, V. V., & Osadcha, K. P. (2015). Modern realities and trends of the development of information and communication technologies in education. Informatsiini tekhnolohii i zasoby navchannia, 4 (48), 47-57. Retrieved from https://journal.iitta.gov.ua/index.php/itlt/article/view/1252. (in Ukrainian)

Nesterenko, O. V., Savenkov, O. I., & Falovskyi, O. O. (2016). Intelligent Systems for Decision-Making Support: Teach. Manual. Kyiv, Ukraine: Natsionalna akademiia upravlinnia. (in Ukrainian)

Starikov, A. (2005). Genetic algorithms – mathematical apparatus. BaseGroup Labs. Retrieved from https://basegroup.ru/community/articles/ga-math. (in Russian)

Fedosin, S. A., Ladyaev, D. A., & Marina, O. A. (2010). Analysis and comparison of methods of neural networks. Vestnik Mordovskogo universiteta. Seriya "Fiziko-matematicheskie nauki", (4), 79-88. (in Russian)

Sharov, S. V. (2015). The Current State of Development of Intelligent Information Systems. Visnyk Chernihivskoho natsionalnoho pedahohichnoho universytetu. Seriia: Pedahohichni nauky, (130), 111-114. (in Ukrainian)

Smith, L. (1996). An Introduction to Neural Networks. Retrieved from http://www.cs.stir.ac.uk/~lss/NNIntro/InvSlides.html. (in English)

Published
2018-09-30
How to Cite
Osadchyi, V., Kruglyk, V., & Bukreyev, D. (2018). Development of a software product for forecasting the entrance of applicants to higher educational institutions. Ukrainian Journal of Educational Studies and Information Technology, 6(3), 55-69. https://doi.org/10.32919/uesit.2018.03.06