Economic Mathematical Modeling of Agrarian Industry Development by Cluster Analysis

Authors

  • Sergey I. Tkachev
  • Ekaterina V. Berdnova
  • Svetlana N. Rubtsova
  • Tatiana Vl. Pakhomova
  • Julia Vl. Lazhauninkas
  • Lyudmila An. Sleptsova

Keywords:

farming innovations, stock raising, crop farming, key function, cluster analysis, economic mathematical model

Abstract

1. Purpose. The main kind of encouraging the development of agrarian industry is financial backing. The state allocates the means to the regions, while the regions distribute them for various needs as planned. In this case a subjective approach to solving the problem in question is possible. To make this process more objective, the scientific method of distributing investments is suggested. 2. Methods. The economic mathematical modeling of agrarian industry development by cluster analysis is suggested for the scientific distribution of investments. 3. Results. The key function of commercial activities in agrarian industry is the income from introducing research (innovations) characterized by respective parameters (arguments). In crop farming they include efficient rotation, fertilizers, seed fund, weed control. In stock raising they include immunologic prophylaxis problems, ensilage conservation, etc. Eventually, the investments optimally distributed in the Saratov oblast’ included 635,271 thousand rubles for crop farming and 915,227 thousand rubles for stock raising. The specific result is that the investments are distributed in the region up to a specific amount by the scientific method with the help of cluster analysis. 4. Conclusion. The goal set forth to determine the scientific method has been achieved, which is proven by the specific data on crop farming and stock raising. The specific conclusion is that the problem with distributing investments in the studied region is solved scientifically. The distribution of population across the studied territory is a factor difficult to consider in terms of investments distribution. There are no convincing average arithmetic and statistic figures. This is why, cluster analysis was used instead. In this procedure the population’s need for investments is tied to clusters of homogeneous communities (towns) and the weighted average condition by clusters is determined graphically (see Fig. 1). The further distribution of investments is planned proceeding from this condition.

Published

2020-02-01

Issue

Section

Artigos e Ensaios