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

M. Al-Gunaid,M. Shcherbakov,V. V. Trubitsin,A. M. Shumkin

Published 2018 in International Conference on Information, Intelligence, Systems and Applications

ABSTRACT

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.

PUBLICATION RECORD

  • Publication year

    2018

  • Venue

    International Conference on Information, Intelligence, Systems and Applications

  • Publication date

    2018-07-01

  • Fields of study

    Agricultural and Food Sciences, Computer Science

  • Identifiers
    DOI 10.1109/IISA.2018.8633610
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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