Time series analysis sales of sowing crops based on machine learning methods

被引：0

作者：

Al-Gunaid, Mohammed A. ^{[1
]}

Shcherbakov, Maxim, V ^{[1
]}

Trubitsin, Vladislav V. ^{[1
]}

Shumkin, Alexandr M. ^{[1
]}

机构：

[1] Volgograd State Tech Univ, Volgograd, Russia

来源：

2018 9TH INTERNATIONAL CONFERENCE ON INFORMATION, INTELLIGENCE, SYSTEMS AND APPLICATIONS (IISA) | 2018年

关键词：

forecasting; agro-industry; agroindustrial complex; sales volume; yield; random forest; neural network; linear regression; correlation analysis; FUZZY COGNITIVE MAPS; YIELD;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

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.

引用

页码：106 / 111

页数：6

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