DOI:

https://doi.org/10.14483/22484728.9872

Published:

2014-11-26

Issue:

Vol. 8 No. 2 (2014)

Section:

A Research Vision

Benchmarking among artificial intelligence techniques applied to forecast

Authors

  • Cristhian Johnatan Izquierdo Ortiz
  • Carlos Enrique Montenegro Marin

Keywords:

Demand forecasting, Genetic algorithms, Artificial neural networks, Forecasting methods (es).

Abstract (es)

The article is about creating a space for multiple tests of demand forecasting techniques, this space is a software development where besides to testing the algorithms on the same database, these code routines can be compared with each other, this tool allows generate forecasts to be usable in decision making on purchases of Distribution Companies. Besides comparing forecasting some simple techniques like Moving Average (MM) and Last Period with other techniques such as Artificial Neural Networks (ARN) and genetic algorithms (GA), the comparison is made taking into account the error criteria of generated forecasts and the processing time of the methods. Throughout the article explains the design, development and implementation of the above methods and their integration with the tool.

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How to Cite

APA

Izquierdo Ortiz, C. J., and Montenegro Marin, C. E. (2014). Benchmarking among artificial intelligence techniques applied to forecast. Visión electrónica, 8(2), 55–66. https://doi.org/10.14483/22484728.9872

ACM

[1]
Izquierdo Ortiz, C.J. and Montenegro Marin, C.E. 2014. Benchmarking among artificial intelligence techniques applied to forecast. Visión electrónica. 8, 2 (Nov. 2014), 55–66. DOI:https://doi.org/10.14483/22484728.9872.

ACS

(1)
Izquierdo Ortiz, C. J.; Montenegro Marin, C. E. Benchmarking among artificial intelligence techniques applied to forecast. Vis. Electron. 2014, 8, 55-66.

ABNT

IZQUIERDO ORTIZ, Cristhian Johnatan; MONTENEGRO MARIN, Carlos Enrique. Benchmarking among artificial intelligence techniques applied to forecast. Visión electrónica, [S. l.], v. 8, n. 2, p. 55–66, 2014. DOI: 10.14483/22484728.9872. Disponível em: https://revistas.udistrital.edu.co/index.php/visele/article/view/9872. Acesso em: 30 jun. 2024.

Chicago

Izquierdo Ortiz, Cristhian Johnatan, and Carlos Enrique Montenegro Marin. 2014. “Benchmarking among artificial intelligence techniques applied to forecast”. Visión electrónica 8 (2):55-66. https://doi.org/10.14483/22484728.9872.

Harvard

Izquierdo Ortiz, C. J. and Montenegro Marin, C. E. (2014) “Benchmarking among artificial intelligence techniques applied to forecast”, Visión electrónica, 8(2), pp. 55–66. doi: 10.14483/22484728.9872.

IEEE

[1]
C. J. Izquierdo Ortiz and C. E. Montenegro Marin, “Benchmarking among artificial intelligence techniques applied to forecast”, Vis. Electron., vol. 8, no. 2, pp. 55–66, Nov. 2014.

MLA

Izquierdo Ortiz, Cristhian Johnatan, and Carlos Enrique Montenegro Marin. “Benchmarking among artificial intelligence techniques applied to forecast”. Visión electrónica, vol. 8, no. 2, Nov. 2014, pp. 55-66, doi:10.14483/22484728.9872.

Turabian

Izquierdo Ortiz, Cristhian Johnatan, and Carlos Enrique Montenegro Marin. “Benchmarking among artificial intelligence techniques applied to forecast”. Visión electrónica 8, no. 2 (November 26, 2014): 55–66. Accessed June 30, 2024. https://revistas.udistrital.edu.co/index.php/visele/article/view/9872.

Vancouver

1.
Izquierdo Ortiz CJ, Montenegro Marin CE. Benchmarking among artificial intelligence techniques applied to forecast. Vis. Electron. [Internet]. 2014 Nov. 26 [cited 2024 Jun. 30];8(2):55-66. Available from: https://revistas.udistrital.edu.co/index.php/visele/article/view/9872

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