International Journal of Industrial Engineering and Management

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Vol. 15 No. 1 (2024)
Original Research Article

Application of neural networks in the prediction of the circular economy level in agri-food chains

E. G. Muñoz-Grillo
Universidad Técnica de Manabí, Faculty of Basic Sciences, Portoviejo, Ecuador
Neyfe Sablón-Cossío
Universidad Técnica de Manabí, Grupo de Producción y Servicios, Faculty of Postgraduate, Portoviejo, Ecuador
Sebastiana del Monserrate Ruiz-Cedeño
Universidad Técnica de Manabí, Faculty of Administrative and Economic Sciences, Portoviejo, Ecuador
Ana Julia Acevedo-Urquiaga
Fundación Universitaria San Mateo, Industrial Engineering Program, Bogotá, Colombia
D. A. Verduga-Alcívar
Universidad Técnica de Manabí, Faculty of Basic Sciences, Portoviejo, Ecuador
D. Marrero-González
Universidad Técnica de Manabí, Portoviejo, Ecuador
Karel Diéguez-Santana
Universidad Regional Amazónica, IKIAM, Ecuador

Published 2024-03-11

abstract views: 83 // REFERENCES (PDF): 0


Keywords

  • Neural networks,
  • Circular economy,
  • Agri-food chains,
  • Circular economy level

How to Cite

Muñoz-Grillo, E. G., Sablón-Cossío, N., Ruiz-Cedeño, S. del M., Acevedo-Urquiaga, A. J., Verduga-Alcívar, D. A., Marrero-González, D., & Diéguez-Santana, K. (2024). Application of neural networks in the prediction of the circular economy level in agri-food chains. International Journal of Industrial Engineering and Management, 15(1), 45–58. https://doi.org/10.24867/IJIEM-2024-1-347

Abstract

The objective of the work is to predict the level of circular economy in the agri-food chain through an empirical neural network approach. The research methodology includes the training of a neural network to predict the level of 128 circular economy in two agri-food chains. The novelty of this work lies in the possibility of defining in advance circular strategies based on the prediction of the level of circular economy. Historical data on the level of circular economy are compared with those predicted by neural networks. As a result, it is shown that if the weights of the circular economy level variables are not homogeneous, the procedure has a lower correlation value which, however, remains significant.

Article history: Received (June 29, 2023); Revised (February 9, 2024); Accepted (February 12, 2024); Published online (February 26, 2024)

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