Optimizing Logistics by Using Machine Learning Algorithms

dc.contributor.author	Rakhmonova Maftuna Nabijan qizi
dc.contributor.author	Saida Safibullaevna Beknazarova
dc.date.accessioned	2025-12-28T13:46:25Z
dc.date.issued	2022-05-10
dc.description.abstract	Machine learning algorithms and the models they’re based on excel at finding anomalies, patterns and predictive insights in large data sets. Many supply chain challenges are time, cost and resource constraint-based, making machine learning an ideal technology to solve them. Machine learning and AI-based techniques are the foundation of a broad spectrum of next-generation logistics and supply chain technologies now under development
dc.format	application/pdf
dc.identifier.uri	https://periodica.org/index.php/journal/article/view/108
dc.identifier.uri	https://asianeducationindex.com/handle/123456789/6442
dc.language.iso	eng
dc.publisher	Periodica Journal
dc.relation	https://periodica.org/index.php/journal/article/view/108/94
dc.rights	https://creativecommons.org/licenses/by-nc/4.0
dc.source	Periodica Journal of Modern Philosophy, Social Sciences and Humanities; Vol. 6 (2022): PERIODICAL; 21-23
dc.source	2720-4030
dc.subject	Logistics
dc.subject	Machine
dc.subject	Algorithms
dc.subject	development
dc.title	Optimizing Logistics by Using Machine Learning Algorithms
dc.type	info:eu-repo/semantics/article
dc.type	info:eu-repo/semantics/publishedVersion
dc.type	Peer-reviewed Article

item.page.files

pagination.showing.labelpagination.showing.detail

item.page.filesection.name: qizi_2022_optimizing_logistics_by_using_machine_le.pdf
item.page.filesection.size: 316.08 KB
item.page.filesection.format: Adobe Portable Document Format