Open AccessUsing Neural Network Technologies to Assess the Quality Characteristics of Food
Author(s) -
Vladimir Sadovoy,
T V Voblikova,
A. V. Morgunova
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/852/1/012088
Subject(s) - recipe , artificial neural network , documentation , computer science , quality (philosophy) , self organizing map , artificial intelligence , food composition data , cluster (spacecraft) , composition (language) , data mining , food science , chemistry , linguistics , epistemology , orange (colour) , programming language , philosophy
A 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.