MATHEMATICAL MODELS AND INFORMATION TECHNOLOGIES IN THE REGIONAL AGROINDUSTRIAL COMPLEX

Currently, mathematical modeling and the use of information technologies in the agro-industrial complex (Agro-Industrial Complex) are beginning to play a huge role in the successful functioning of various industries and sectors of the economy. Their introduction into the structure of the agro-industrial complex is dictated primarily by the need to ensure security and create conditions for the favorable functioning of the sphere as a whole. The purpose of the research in this article is to substantiate the effectiveness of using mathematical models and information technologies to optimize the region’s agro-industrial complex in the context of the functioning of the digital economy.

To write this study, the basis was taken from scientific journals that examine the issues of managing innovation in the agro-industrial complex, forecasting the development of firms involved in agriculture, as well as statistical data on the state of the country’s agriculture. The research methods in this work are mathematical modeling, data analysis, system analysis of the agro-industrial complex. One of the most important results of the study is the development of models that optimize agricultural enterprises.

The first of the models takes into account the influence of various factors on the development of the agricultural sector. The second model makes a forecast based on various weather conditions. It is also worth noting that the work examines such an aspect as the use of information technology in the agro-industrial complex, and identifies the main actions for analyzing an enterprise for the level of threats in the information sphere. The theoretical significance of the study lies in the fact that based on the results obtained, it is possible to develop an optimal management strategy for an agro-industrial enterprise.

The practical significance of the work is that, based on the models, it is possible to optimize the use of resources in an enterprise and develop an effective forecast for making management decisions.

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