Article 2321

Title of the article

Designing neural network models using visual programming methods 

Authors

Stanislav A. Yamashkin, Candidate of engineering sciences, associate professor of the sub-department of automated data processing and control systems, Ogarev Mordovia State University (68/1 Bolshevistskaya street, Saransk, Russia), E-mail: yamashkinsa@mail.ru
Anastasiya A. Kamaeva, Student, Ogarev Mordovia State University (68/1 Bolshevitskaya street, Saransk, Russia), E-mail: aakamaeva@yandex.ru 

Index UDK

004.89 

DOI

10.21685/2072-3059-2021-3-2 

Abstract

Background. In the modern world, component development methods are becoming increasingly popular. They allow not only to quickly solve the assigned tasks, but also to meet the high requirements for the performance and reliability of the created software products. The use of the block approach in machine learning is a breakthrough method that makes the development of complex neural network architectures several times easier. The purpose of this work is to study the methods of component development and the technology of graph-symbolic programming for solving the problem of visual programming of neural networks. Materials and methods. The work develops methods and algorithms for configuring neural network models based on software systems that implement a graphical interface for creating neural networks using graph-symbolic programming based on the JavaScript programming language. Results. Comprehensive research has been carried out in the field of visual programming of neural networks using component development methods. A graphical interface has been developed for configuring neural network architectures. Conclusions. The presented approach to visual programming of neural networks simplifies the development process, avoids errors and creates more efficient and reliable systems. 

Key words

visual programming, neural network, machine learning, graphs, neural network architecture, topological graph, graphic-symbolic programming, component development, modular programming 

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References

1. Yamashkin S.A. Yamashkin A.A., Zanozin V.V. Formation of a repository of deep neural networks in the system of digital spatial data infrastructure. Potentsial intellektual'no odarennoy molodezhi – razvitiyu nauki i obrazovaniya: materialy IX Mezhdunar. nauch. foruma molodykh uchenykh, innovatorov, studentov i shkol'nikov = The potential of intellectually gifted youth for the development of science and education:: proceedings of the 9th International scientific forum of young scientists, innovators, students and pupils. Astrakhan, 2020:370–375. (In Russ.)
2. Kamaeva A.A. The current state of artificial neural networks. Innovatsii. Nauka. Obrazovanie = Innovation. Science. Education. 2020;(16):377–387. (In Russ.)
3. Kovartsev A.N., Zhidchenko V.V., Popova-Kovartseva D.A., Abolmasov P.V. Principles of constructing graph-symbolic technology. Otkrytye semanticheskie tekhnologii proektirovaniya intellektual'nykh system = Open semantic technologies for the design of intelligent systems. 2013;(3):195–204. (In Russ.)
4. Morozova T.Yu., Burlachenko T.B. A solution of the forecasting problem in systems with a high degree of uncertainty. Izvestiya TRTU = Proceedings of TRTU. 2006; (9-2):169. (In Russ.)
5. Gafarov F.M., Galimyanov A.F. Iskusstvennye neyronnye seti i prilozheniya: ucheb. posobie = Artificial neural networks and applications: textbook. Kazan: Izd-vo Kazan. un-ta, 2018:121. (In Russ.)
6. Bubnov I. What is modular programming and who needs it. Geek-Brains. (In Russ.). Available at: https://geekbrains.ru/posts/module_programming/
7. Kirichenko A.A. Neyropakety – sovremennyy intellektual'nyy instrument issledovatelya: ucheb. posobie = Neuropackages – a modern intellectual tool for the researcher: textbook. Moscow, 2013:297. (In Russ.). ISBN 978-5-9904911-1-3.
8. Kovartsev A.N., Zhidchenko V.V., Popova-Kovartseva D.A. Metody i tekhnologii vizual'nogo programmirovaniya: ucheb. posobie = Methods and technologies of visual programming: textbook. Samara: Ofort, 2017:197. (In Russ.)
9. Lomakin V.V. Programmirovanie i programmnoe obespechenie informatsionnykh tekhnologiy: ucheb. posobie = Information technology programming and software: textbook. Belgorod: Izd-vo BelGU, 2010:114. (In Russ.)
10. Tyugashev A.A. Graficheskie yazyki programmirovaniya i ikh primenenie v sistemakh upravleniya real'nogo vremeni = Graphic programming languages and their application in real-time control systems. Samara: Izd-vo Samarskogo nauchnogo tsentra RAN, 2009:98. (In Russ.)
11. Lomakin V.V. Programmirovanie i programmnoe obespechenie informatsionnykh tekhnologiy: ucheb. posobie = Information technology programming and software: textbook. Belgorod: Izd-vo BelGU, 2010:114. (In Russ.)
12. Zhidchenko V.V. Software complex for modeling and analysis of parallel computing algorithms. PhD dissertation. Samara, 2007:189. (In Russ.)
13. Vlasov A.I. System analysis of technological processes for the production of complex technical systems using visual models. Mezhdunarodnyy nauchno-issledovatel'skiy zhurnal = International scientific and research journal. 2013;(10-2):17. (In Russ.)

 

Дата создания: 09.12.2021 08:46
Дата обновления: 09.12.2021 09:22