A COMBINED APPROACH TO FORECASTING AGRICULTURAL PRODUCTION IN AN ORGANIZATION

DOI 10.32651/268-146

Issue № 8, 2026, article № 19, pages 147-154

Section: Problems of agroeconomic researches

Language: Russian

Original language title: КОМБИНИРОВАННЫЙ ПОДХОД К ПРОГНОЗИРОВАНИЮ ПРОИЗВОДСТВА ПРОДУКЦИИ СЕЛЬСКОГО ХОЗЯЙСТВА В ОРГАНИЗАЦИИ

Keywords: COMBINED APPROACH, FORECASTING, AGRICULTURAL PRODUCTION, AGRICULTURAL ORGANIZATION, ACCURACY, MACHINE LEARNING

Abstract: The article is devoted to the development of combined forecasting methodology. The relevance of the research is determined by the need to improve the tools for forecasting agricultural production, mainly in medium-sized and small agricultural organizations in order to optimize acreage and effective financial planning. Currently, there are practically no approaches based on the combined use of traditional and advanced methods of forecasting agricultural production. The purpose of the study is to form a combined methodological approach to forecasting agricultural production in an organization based on a combination of classical and modern methods. The results of the study are: a combined methodological approach to forecasting agricultural production in an organization based on the combined use of detailed simulation and calculation models, econometric methods, expert assessment methods and machine learning, as well as its testing using the example of an agricultural organization in the Altai Territory (LLC "Solton"). It is determined that the proposed methodological approach will improve the accuracy of forecasting agricultural production in the organization. The use of the research results may further increase the accuracy of forecasting agricultural production in other agricultural organizations, including in other regions.

Authors: Sannikova Inna Nikolaevna, Kraiushkin Maksim Gennadevich, Slivnyi Dmitrii Igorevich