Sale forecast for basic commodities based on artificial neural networks prediction
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...
- Autores:
-
silva d, jesus g
Jesús Vargas Villa
Cabrera, Danelys
- Tipo de recurso:
- http://purl.org/coar/resource_type/c_f744
- Fecha de publicación:
- 2019
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/5129
- Acceso en línea:
- https://hdl.handle.net/11323/5129
https://repositorio.cuc.edu.co/
- Palabra clave:
- Artificial Neural Networks (ANN)
Commodities
Sales forecast
- Rights
- openAccess
- License
- CC0 1.0 Universal
| Summary: | 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. |
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