Russian Federation
Russian Federation
This article discusses the development of an algorithmic approach to demand forecasting in retail, followed by integration into an enterprise information system. Classic statistical methods and modern machine learning algorithms are considered from the perspective of their computational implementation. The results of the study demonstrate that integrating forecasting algorithms into an enterprise information system improves the accuracy of demand planning and reduces inventory management costs.
demand forecasting, algorithm, information system, machine learning, data analysis, retail, automation
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