PROSPECTS FOR AGRICULTURAL PRODUCTION IN HOUSEHOLDS OF THE MAHALLA SYSTEM IN UZBEKISTAN

Abstract

In this study, the factors affecting the volume of fruit, vegetable and berry production were analyzed using econometric and artificial neural network (ANN) models. The results of the study confirmed that factors such as population, income, prices, cultivated area and productivity have a significant impact on the volume of production. The econometric model made it possible to identify statistical relationships between factors and the resulting indicator and explain their economic content.

At the same time, the ANN model showed high efficiency in identifying complex and nonlinear relationships and demonstrated superior results in terms of forecasting accuracy compared to traditional regression models. The learning ability of the model made it possible to identify hidden patterns in historical data and reliably estimate future production volumes.