Automated system-cognitive analysis of the dependence of export and import of agricultural machinery on its production (the case of Russia)

Abstract

The issue raised in the article is the study of the dependence of export and import of agricultural machinery on its production in Russia. The Russian agricultural machinery market is influenced by three groups of factors: 1) own production of agricultural machinery; 2) export of agricultural machinery of Russian production; 3) import of agricultural machinery of foreign production. Traditionally, such problems are solved using multivariate analysis. However, in this case, the use of this method is problematic for a number of reasons: the source data is dimensional and measured in different units, the number of observations is less than the number of factors, the factors depend on each other, and the number of factors is too large. These restrictions are proposed to be overcome by applying automated system-cognitive analysis and its software tools of the intellectual system "Eidos". For this purpose the following tasks were solved: 1) formulation of the idea and the concept of problem solving; 2) justification of the choice of the method and tool for solving the problem; 3) application of the selected method and tool to solve the problem; 4) evaluation of the effectiveness of the proposed solution of the problem; 5) consideration of the restrictions and disadvantages of the proposed solution of the problem and the prospects for its development by overcoming these restrictions and disadvantages. Some results of solving these problems are briefly summarized in this article.

Cognitive Model of Regional Agricultural Sector

“…We suggest constructing an integrated cognitive model of the agricultural sector that would combine the cognitive model of the object and the static and dynamic models of the agricultural sector environment. Cognitive modeling is based on the findings of Russian and foreign scientists presented in [8][9][10][11][12][13][14][15][16].…”