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Please use this identifier to cite or link to this item: https://dspace.ncfu.ru/handle/20.500.12258/18241
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dc.contributor.authorSadovoy, V. V.-
dc.contributor.authorСадовой, В. В.-
dc.date.accessioned2021-11-10T07:38:12Z-
dc.date.available2021-11-10T07:38:12Z-
dc.date.issued2021-
dc.identifier.citationSadovoy, V.V., Voblikova, T.V., Morgunova, A.V. Using neural network technologies to assess the quality characteristics of food // IOP Conference Series: Earth and Environmental Science. - 2021. - Том 852. - Выпуск 127. - Номер статьи 012088. - DOI 10.1088/1755-1315/852/1/012088ru
dc.identifier.urihttp://hdl.handle.net/20.500.12258/18241-
dc.description.abstractA method for assessing the recipe composition of multicomponent food products (for example, meat products) based on the results of studying the chemical and amino acid compositions of final products has been developed. The proposed method is based on the use of artificial intelligence to create a data array using neural networks and the assessment of compositions by cluster analysis of Kohonen networks-to determine the compliance of the recipe composition with the technical documentation indicators.ru
dc.language.isoenru
dc.publisherIOP Publishing Ltdru
dc.relation.ispartofseriesIOP Conference Series: Earth and Environmental Science-
dc.subjectNeural network technologiesru
dc.subjectQuality characteristics of foodru
dc.titleUsing neural network technologies to assess the quality characteristics of foodru
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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