The purpose of the research is to develop and computer implementation of methods of data mining based on cognitive modeling, obtained as a result of matrix modeling and assessment of the level of food security (FS) in conditions of forced import substitution and increased food exports. As the basic methodology for obtaining an objective assessment of the FS level, a systemic approach was used, as well as separate methods of analysis and structural synthesis of elements of the modeling system. The identification of specific differences of the updated FS Doctrine (2020) was carried out using the method of comparative research. Fuzzy cognitive maps (FCMs) were used as a basic modeling tool. The construction of the graph structure, relationships and weights of the FCM was carried out by means of a previously formed system of indicators. It has been shown that to solve the problem of objective assessment of the FS level, it is advisable to use computer modeling based on fuzzy production cognitive maps. The advisability of integral consideration of key groups of factors is justified: food production, consumption, as well as the share of imports and the rational amount of food reserves in conditions of forced import substitution. The directions of computer system modernization and improvement of mining methods for level prediction are presented. An example of FCM and a diagram of the evolution of the FS support system in pandemic conditions are given.

No abstract

No abstract

No abstract