Forecasting corn production indicators in the Republic of Srpska

Abstract

The aim of this paper is to formulate quantitative models to predict future trends in corn production in the Republic of Srpska. The applied research methods are the descriptive analysis method, and the analytical statistical method, i.e. the Box-Jenkins Model based on the ARIMA model (Autoregressive Integrated Moving Average). The results of the research show that the corn production indicators, as the most important crop in the Republic of Srpska, will, despite the oscillations, show an increase in the last year of the five-year prediction period (2018-2022) compared to the previously analysed twenty-two year period (1996-2017). The formulation of such forecasting models is a good basis for planning the overall crop production in the Republic of Srpska.

Influence of Total Production on the Planting Structure of Significant Vegetable Crops in the Republic of Serbia

“…Descriptive statistics and analytical methods were employed as appropriate to the objectives of this study (Nedeljković et al 2019). Standard descriptive statistics tools were used for processing the parameter values observed.…”

Applicability of machine learning models using a neural network for predicting the parameters of the development of food markets

“…We find a limited number of publications on the study of forecasting issues using ANN methods (Nedeljković et al, 2019;Abbasimehr et al, 2020;Marston et al, 2021) and almost complete absence on forecasting consumption volumes, demand and prices in agri-food markets. In accordance with this, in this work, the authors have attempted to fill this gap.…”