Time Series Analysis Sales of Sowing Crops Based on Machine Learning Methods

摘要

The main purpose of this paper is to identify factors that affect sales volumes of sowing crops and develop a method for the most accurate forecasting of their sales to support decision making and improve the efficiency of business processes of agro-industrial companies. This article describes the developed approach to the forecasting of sales volumes of sowing crops, which includes the identification of factors that affect sales, the formation of a training sample, and a comparison of methods for constructing mathematical models. For the construction of forecasts, linear regression methods, random forests and a neural network are used. Also, the article describes a software platform that builds forecasts of sales of crops, using R and ShinyApps.