Труды Кубанского государственного аграрного университета


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2019, № 79

UDC: 004.9:338.43
GSNTI: 28.17.19

Prospects for application of methods and means of simulation in the agrarian field

Simulation is one of the most effective research methods based on the modeling of various processes, among which are processes associated with the agricultural activities of agricultural enterprises. At the same time, the specifics of these processes depends on the type of sub-industry affiliation, as well as the multitude of various factors of the internal and external environment influencing it that arise during the planning, organization of production and sales of products. The paper identifies the main areas of the agricultural industry in which the most effective use of methods and their corresponding tools. As a result of the study, it was found that the use of simulation tools in the agricultural sector is feasible in the study of the characteristics of the processes at the stage of processing crop products, which to a greater extent consist in a lesser attachment to seasonal conditions. In addition, the variety of types of cultivated crops and the greater variety of species of the final processed, and at the same time options for the implementation of processing technologies, determine various ways of organizing processes. An analysis of the features of their flow by means of simulation modeling will reveal bottlenecks that reduce the efficiency of the entire processing process, as well as optimize it if necessary. Among the software tools offered on the market, the systems of foreign companies are the most advanced and widespread. In fact, they differ from each other both in the field and field of application, and in additional functional capabilities, as well as in the ways of representing the studied simulated systems. Therefore, these funds are as close as possible for the analysis of agricultural processing processes.
Keywords: Simulation, modeling of processes and systems, processes of agricultural enterprises, uncertainties, data analysis
DOI: 10.21515/1999-1703-79-55-60

References:

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Authors:

  1. Osenniy Vitaliy Vital’evich, Phd in Economics, associate Professor; Department of economic Cybernetics, Federal State Budgetary Educational Institution of Higher Education “I.T. Trubilin Kuban State Agrarian University”.
  2. Frantsisko Olga Yur’evna, Phd in Economics, associate Professor; Department of economic Cybernetics, Federal State Budgetary Educational Institution of Higher Education “I.T. Trubilin Kuban State Agrarian University”.