Demand forecasting method using artificial neural networks

Based on a forecast, the decision maker can determine the capacity required to meet a certain forecast demand, as well as carry out in advance the balance of capacities in order to avoid underusing or bottlenecks. This article proposes a procedure for forecasting demand through Artificial Neural Networks. In order to carry out the validation, the procedure proposed was applied in a Soda Trading and Distribution Company where three types of products were selected

• Autores: amelec, viloria; Arrieta Matos, Fernanda; Gaitán, Mercedes; Hernández Palma, Hugo; Flórez Guzman, Yasmin; CABAS VASQUEZ, LUIS CARLOS; Vargas Mercado, Carlos; Pineda Lezama, Omar Bonerge
• Tipo de recurso: http://purl.org/coar/resource_type/c_816b
• Fecha de publicación: 2019
• Institución: Corporación Universidad de la Costa
• Repositorio: REDICUC - Repositorio CUC
• Idioma: eng
• OAI Identifier: oai:repositorio.cuc.edu.co:11323/5869
• Acceso en línea: http://hdl.handle.net/11323/5869; https://repositorio.cuc.edu.co/
• Palabra clave: Forecast; Artificial Neural Networks; Big Data; Demand; Pronóstico; Redes neuronales artificiales; Big Data; Demanda
• Rights: openAccess
• License: http://creativecommons.org/publicdomain/zero/1.0/