FOOD SECURITY MANAGEMENT BY MACHINE LEARNING METHODS IN THE INFORMATION SPACE OF THE AGRICULTURAL AND INDUSTRIAL COMPLEX

Background. The paper considers a refined statement of the problem of food security management in the formation of a digital economy, developed on the basis of a probabilistic assessment of the implementation of organizational, organizational, resource, technical and technological processes for ensuring food security using a universal methodology. Materials and methods. Methods and technologies for applying machine learning in the tasks of ensuring and managing food security based on data from the information space of the digital economy are given. A methodology and methods are proposed for assessing and forecasting threats, assessing the vulnerability of economic systems and choosing the optimal strategy to counter them. Results and conclusions. Algorithms and the most suitable programming languages for the implementation of the solutions of the set task have been selected. It is noted that all this is possible only if there is an information space organized in accordance with the paradigm of the digital economy.