CONCEPTUAL IDENTIFICATION OF THE AGRICULTURAL MACROREGION AS AN OBJECT OF CONTROL OF SPATIAL DEVELOPMENT OF PRODUCTION BY MACHINE LEARNING METHODS IN THE INFORMATION SPACE OF THE DIGITAL ECONOMY

DOI 10.32651/222-62

Issue № 2, 2022, article № 11, pages 62-68

Section: Problems of agroeconomic researches

Language: Russian

Original language title: КОНЦЕПТУАЛЬНАЯ ИДЕНТИФИКАЦИЯ СЕЛЬСКОХОЗЯЙСТВЕННОГО МАКРОРЕГИОНА, КАК ОБЪЕКТА УПРАВЛЕНИЯ ПРОСТРАНСТВЕННЫМ РАЗВИТИЕМ ПРОИЗВОДСТВА МЕТОДАМИ МАШИННОГО ОБУЧЕНИЯ В ИНФОРМАЦИОННОМ ПРОСТРАНСТВЕ ЦИФРОВОЙ ЭКОНОМИКИ

Keywords: SPATIAL DEVELOPMENT, MACROREGION, AGRICULTURAL ECONOMY, ANALYSIS, STATE GRAPHS OF COMPLEX SYSTEMS, DIFFERENTIAL AND DIFFERENCE EQUATIONS, MATHEMATICAL MODELS, NEURAL NETWORKS, INFORMATION SPACE, FORECASTING AND MANAGEMENT OF AGRICULTURAL SYSTEMS

Abstract: The presented work examines methods of conceptual identification, forecasting of behaviour and identification of characteristic models of development and functioning of agricultural macroregions, as well as managing the production of machine learning and artificial intelligence information technologies in the spatial development of the agricultural digital economy, based on dynamic technologies and mathematical methods of neural networks, implemented by certain means using computer technology related to modern language programming methods: Python and Scala in combination with standard libraries ‒ Pandas and Tensor Flow. And for effective analysis of qualitative characteristics of dynamics of evolution of economic systems there is presented a method of constructing their characteristic graphs and matrices of contiguity by linearisation of processes in a limited neighborhood using a two-layer neural network and directions of their implementation are given.

Authors: Semkin Aleksandr Grigorevich, Voronin Evgenii Alekseevich