Rybalka, A. I.Kutsenko, A. S.Kovalenko, S. V.2021-03-042021-03-042020Rybalka A. I. Modelling of an automated food quality assessment system based on fuzzy inference / Kutsenko A. S., Kovalenko S. V., Kovalenko S. M. // VII International Scientific and Technical Conference Metrology, information measuring technologies and systems: theses of reports, 18-19 February 2020.- Kharkov: KHNURE, 2020.- p.73-74.http://openarchive.nure.ua/handle/document/14769The purpose of this study is to create a methodology for developing an automated system for assessing the quality of food products based on a comprehensive quality indicator and the use of fuzzy logic theory, namely, fuzzy inference. In our opinion, such an approach to quality assessment can reduce the subjective component that has a significant impact on making a final decision. The system, built on a given algorithm, allows us to assess the quality of food products, taking into account the data of laboratory studies on measurable quality indicators and expert opinions on difficult to measure indicators.enquality of foodquality indicatorfuzzy logic theoryfuzzy inferenceThesis