Algorithms for Thermal Control Systems with Artificial Intelligence Based on Fuzzy Logic

dc.contributor.author	Nigmatov Azizjon Makhkamovich
dc.contributor.author	Yunusova Sayyora Toshkenboevna
dc.date.accessioned	2026-01-01T12:11:59Z
dc.date.issued	2024-03-21
dc.description.abstract	Drying cotton and cotton raw materials is an important step in their production, requiring significant energy consumption. This article discusses methods for improving energy efficiency in cotton drying. In particular, schemes and formulas are presented for optimizing the drying process using modern technologies and energy saving methods
dc.format	application/pdf
dc.identifier.uri	https://zienjournals.com/index.php/tjm/article/view/5123
dc.identifier.uri	10.62480/tjms.2024.vol30.5123.pp22-27
dc.identifier.uri	https://asianeducationindex.com/handle/123456789/63498
dc.language.iso	eng
dc.publisher	Zien Journals
dc.relation	https://zienjournals.com/index.php/tjm/article/view/5123/4206
dc.rights	https://creativecommons.org/licenses/by-nc/4.0
dc.source	Texas Journal of Multidisciplinary Studies; Vol. 30 (2024): TJM; 22-27
dc.source	2770-0003
dc.subject	Electricity
dc.subject	drying
dc.subject	energy saving
dc.subject	efficiency
dc.title	Algorithms for Thermal Control Systems with Artificial Intelligence Based on Fuzzy Logic
dc.type	info:eu-repo/semantics/article
dc.type	info:eu-repo/semantics/publishedVersion
dc.type	Peer-reviewed Article

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