Our website uses cookies. By continuing to use this site, you agree to our use of cookies in accordance with this notice and the Terms of Use.
Journals
Books
Monographies Textbooks
Submit manuscript
MONITORING AND EXPERTISE IN SAFETY SYSTEM
Journals / MONITORING AND EXPERTISE IN SAFETY SYSTEM / Issue 4, 2024 / COMPUTER MODELS OF ARTIFICIAL INTELLIGENCE SYSTEMS BASED ON NEURAL NETWORKS
UDC 004

COMPUTER MODELS OF ARTIFICIAL INTELLIGENCE SYSTEMS BASED ON NEURAL NETWORKS

Published in MONITORING AND EXPERTISE IN SAFETY SYSTEM · Pages 32–38 · Rubric: DIALOGUES WITH SPECIALISTS
DOI: https://doi.org/10.61260/2304-0130-2024-4-32-38
Received: 26.10.2024 Accepted: 19.11.2024 Published: 31.12.2024
Authors
AL
Alexander Y. Labinsky
SPIN
OL
Oleg Pantyukhin
ABSTRACT
The possibilities of artificial neural networks as a basis for creating artificial intelligence systems are considered. The main advantage of artificial neural networks is their ability to learn, generalize, and identify hidden dependencies in the source data. The peculiarities, classification, and methods of training artificial neural networks and the tasks successfully solved using these networks are presented. The stages of solving various problems using artificial neural networks are considered. The features of fuzzy neural networks, deep neural networks, and convolutional neural networks are considered in detail. The following examples of intelligent systems developed on the basis of artificial neural networks are considered: a system for approximating functions from noisy data, a system for classifying large amounts of data, an automatic control system, a cryptographic system, and an image recognition system. Computer models of these systems have been developed, implemented as computer programs. The results of the work of the considered intelligent systems are presented in a visual graphical form.
KEYWORDS
artificial intelligence, artificial neural networks, fuzzy neural networks, deep neural networks, convolutional neural networks, computer models, function approximation, classification, automatic control, cryptographic system, image recognition
Text References
Text
Text (PDF)
Read Download
Text (PDF)
Read Download

1. Maksimov V.I., Kachaev S.V. Cognitive technologies for management decision support. M.: Proceedings of the IPU, 2018. Vol. 1.

2. Dimitrichenko D.P., Zhidkov R.A. The use of neural networks to solve data processing problems in the construction of cognitive maps // News of the Kabardino-Balkarian scientific center of the russian academy of sciences. 2017. № 6.

3. Anderson C.H. The self-organizing map // Neural Computation. 2012. Vol. 5.

4. Barron A.R. Neural net approximation // IEEE Transaction on Information Theory. 2013. Vol. 49.

5. Vapnik V.N. A fuzzy neural network model // IEEE Transactions on Neural Networks. 2017. Vol. 3. № 5.

6. Labinsky A.Yu. Approximation of functions of many variables by a fuzzy neural network // Natural and man-made risks (physico-mathematical and applied aspects). 2017. № 2. P. 6–14.

7. Labinsky A.Yu. Usage of neural networks for solving classification problems // Natural and man-made risks (physico-mathematical and applied aspects). 2017. № 4. P. 25–32.

8. Labinsky A.Yu. The use of fuzzy logic and neural networks in automatic control systems // Scientific and analytical journal «Vestnik Saint-Petersburg university of State fire service of EMERCOM of Russia». 2019. № 1. P. 11–17.

9. Labinsky A.Yu. Neural networks and information security // Problems of risk management in the technosphere. 2019. № 1. P. 16–24.

10. Labinsky A.Yu. Features of using a neural network for image recognition // Problems of risk management in the technosphere. 2016. № 3. P. 21–27.

PDF Text JATS XML
The contact persons
Secretary, editor of the editorial department of the editorial department of the Center for the organization of scientific research and editorial activities Saint-Petersburg university of State fire service of EMERCOM of Russia
Polina Bolotova
associate professor of the department of supervisory activities (responsible for the issue) Saint-Petersburg university of State fire service of EMERCOM of Russia
Tatiana Kuzmina
3514
downloads
Indexing information will be added later
© journals.igps.ru
Agreement Personal data protection and processing policy Support Powered by Editorum, 2026 Instructions
Login or Create
* Forgot your password?