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Please use this identifier to cite or link to this item: https://dspace.ncfu.ru/handle/123456789/27483
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dc.contributor.authorRudakova, T. A.-
dc.contributor.authorРудакова, Т. А.-
dc.date.accessioned2024-04-22T14:23:09Z-
dc.date.available2024-04-22T14:23:09Z-
dc.date.issued2024-
dc.identifier.citationKuyukova, V.N., Rudakova, T.A. Neural Networks in Production // Proceedings of the 2024 Conference of Young Researchers in Electrical and Electronic Engineering, ElCon 2024. - 2024. - pp. 414-417. - DOI: 10.1109/ElCon61730.2024.10468508ru
dc.identifier.urihttps://dspace.ncfu.ru/handle/123456789/27483-
dc.description.abstractThe article presents a new approach to the use of neural networks in logistics. The study suggests using neural networks at every stage of the product creation path, starting from production and ending with delivery to the consumer. The article presents the potential application of neural networks for optimizing warehouse processes, inventory management, demand forecasting and optimal delivery routes.ru
dc.language.isoenru
dc.relation.ispartofseriesProceedings of the 2024 Conference of Young Researchers in Electrical and Electronic Engineering, ElCon 2024-
dc.subjectAutomationru
dc.subjectLogisticsru
dc.subjectNeural networksru
dc.titleNeural Networks in Productionru
dc.typeСтатьяru
vkr.instИнститут сервиса, туризма и дизайна (филиал) СКФУ в г. Пятигорскеru
Appears in Collections:Статьи, проиндексированные в SCOPUS, WOS

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