ON ISSUES OF MONITORING THE ECONOMIC MECHANISM OF THE PUBLIC ADMINISTRATION OF FOOD SECURITY

Abstract

The aim of the article is to research issues of monitoring the economic mechanism of state food security management and build a reasonable model of the interaction of economic mechanism monitoring indicators with the system of public administration of food security. It is substantiated that the functioning of public administration mechanisms aimed at solving the priority problems of society, in particular, such as the decrease in the level of food security due to the full-scale invasion of Russian troops in Ukraine, should be based on the principles of prompt response to the indicators of an effective monitoring system of the economic mechanism of state management of food security. The research methodology includes methods of theoretical knowledge of processes and phenomena, in particular fundamental research of the impact of monitoring performance on the system of state management of food safety and scientific modeling to reflect systemic interrelationships in the conceptual structure of state management when building an adaptive model. The scientific novelty: for the first time, an adaptive neural network model of the interaction of economic mechanism monitoring indicators with the state food security management system has been developed. The adaptability of the model is manifested in the possibility of taking into account dynamic changes in the composition and nature of monitoring indicators of the economic mechanism through the use of neuro-like data processing, which consists in adjusting monitoring indicators based on data processed within the limits of conditional neurocontrollers. Conclusions. The proposed adaptive neural network model of the interaction of the monitoring indicators of the economic mechanism with the system of state management of food security allows a reasoned approach to the management process, strengthens the influence of state management measures aimed at ensuring food security through monitoring results and contributes to the prevention of a food crisis. Considering the scale of information flows in the field of public administration and the need to use artificial neurons to ensure the adaptability and high efficiency of this model, it is important to develop appropriate software capable of implementing the proposed algorithms, which is a perspective for further research.