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Sale Forecast for Basic Commodities Based on Artificial Neural Networks Prediction

Acceso Cerrado
ID Minciencias: ART-0001425442-10
Ranking: ART-GC_ART

Abstract:

The objective of this paper is to carry out the comparison and selection of a method to forecast sales of basic food products efficiently. The source of data comes from a set of popular markets in the main departments of Colombia. The methods and methodologies used are: Hold Method, Winters, the Box Jenkins methodology (ARIMA) and an Artificial Neural Network. The results show that the artificial neural network obtained a better performance achieving the lowest mean square error.

Tópico:

Stock Market Forecasting Methods

Citaciones:

Citations: 4
4

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Información de la Fuente:

SCImago Journal & Country Rank
FuenteAdvances in intelligent systems and computing
Cuartil año de publicaciónNo disponible
VolumenNo disponible
IssueNo disponible
Páginas37 - 43
pISSNNo disponible
ISSN2194-5357

Enlaces e Identificadores:

Publicaciones editoriales no especializadas