Russian Federation
Russian Federation
The article discusses the main types of neural networks that differ in the type of learning: learning with a teacher, learning without a teacher, and reinforcement learning. The basic principles of operation for each type are considered, examples of integration into information systems are proposed, indicating companies already using similar technologies.
artificial intelligence, integration, information systems, neural network, models
1. Sumin, V. I. Ispol'zovanie situacionnogo modelirovaniya v razrabotke sistem prinyatiya resheniy dlya slozhnyh organizacionnyh sistem / V. I. Sumin, A. S. Kravchenko, A. V. Tolkachev // Modelirovanie sistem i processov. – 2024. – T. 17, № 3. – S. 71-79. – DOIhttps://doi.org/10.12737/2219-0767-2024-69-77. – EDN FBBHJO.
2. Bantyukov, S. M. Sozdanie intellektual'noy sistemy upravleniya kachestvom predpriyatiya «Etalon» v aviacionnoy promyshlennosti / S. M. Bantyukov // Modelirovanie sistem i processov. – 2024. – T. 17, № 2. – S. 15-23. – DOIhttps://doi.org/10.12737/2219-0767-2024-17-2-15-23. – EDN YHXUPY.
3. Dmitriev, E. A. Matematicheskoe modelirovanie i realizaciya informacionno-raschetnyh zadach «maskirovka» / E. A. Dmitriev, A. F. Tarakanov, E. A. Shipilova // Modelirovanie sistem i processov. – 2024. – T. 17, № 2. – S. 32-42. – DOIhttps://doi.org/10.12737/2219-0767-2024-17-2-32-42. – EDN DJJKYT.
4. Vybor kriteriya optimal'nosti pri prinyatii upravlencheskih resheniy v slozhnyh tehnicheskih sistemah / A. V. Skrypnikov, I. A. Vysockaya, S. A. Evdokimova [i dr.] // Modelirovanie sistem i processov. – 2024. – T. 17, № 1. – S. 120-128. – DOIhttps://doi.org/10.12737/2219-0767-2024-17-1-120-128. – EDN MMIAIH.
5. Sazonova, S. A. Modelirovanie processa diagnostiki utechek na osnove dvuhal'ternativnoy gipotezy s uchetom pomeh ot stohastichnosti potrebleniya v gidravlicheskoy sisteme / S. A. Sazonova, I. V. Scherbakova, G. I. Smetankina // Modelirovanie sistem i processov. – 2024. – T. 17, № 1. – S. 111-120. – DOIhttps://doi.org/10.12737/2219-0767-2024-17-1-111-120. – EDN CSKRIZ.
6. Matematicheskoe obespechenie informacionno-upravlyayuschey sistemy dlya hraneniya produkcii s ogranichennym srokom hraneniya / D. V. Arapov, N. Yu. Yudina, V. A. Kuricyn, L. A. Korobova // Modelirovanie sistem i processov. – 2024. – T. 17, № 1. – S. 7-18. – DOIhttps://doi.org/10.12737/2219-0767-2024-17-1-7-18. – EDN CXBIVK.
