Determining the Level of Risk for Food Safety in a Fuzzy Environment with the Help of Z Numbers
DOI:
https://doi.org/10.52171/2076-0515_2022_14_01_117_124Keywords:
forecasting, fuzzy sets, Z numbers, inference, linguistic variables, rule base, fuzzy systemAbstract
Article discusses a fuzzy system based on Z numbers to determine the level of food safety risk. This system is widely used to measure food safety risk in many countries around the world. Using grain productivity, grain production and economic growth as input parameters, the food safety risk level of products is assessed and a framework of guidelines is developed. The relationship between input and output variables is described using Z-digit values. The system has been tested in recent years using statistics from the Global Security Index database. A lot of work has been done to predict the level of food safety risk, based on the Z-number system, rules and statistics. The obtained results support the application of the advanced system in real conditions. In this study, food safety risk was forecasted and food safety risk was assessed. Thus, the study reflected the alternatives of food safety risk statistics and the selection of the best alternative for the system to be developed based on certain characteristics.
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.