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Improving Demand Forecasting by Implementing Machine Learning in Poultry Production Company
dc.contributor.author | Garcia Arismendiz, Joaquin Antonio | |
dc.contributor.author | Huertas Zúñiga, Sandra Larissa | |
dc.contributor.author | Lizárraga Portugal, Carlos Augusto | |
dc.contributor.author | Quiroz Flores, Juan Carlos | |
dc.contributor.author | García López, Yván Jesús | |
dc.contributor.other | Lizárraga Portugal, Carlos Augusto | |
dc.contributor.other | Quiroz Flores, Juan Carlos | |
dc.contributor.other | García López, Yván Jesús | |
dc.date.accessioned | 2023-03-28T16:51:56Z | |
dc.date.available | 2023-03-28T16:51:56Z | |
dc.date.issued | 2023 | |
dc.identifier.citation | Garcia-Arismendiz, J., Huertas-Zúñiga, S., Lizárraga-Portugal, C. A., Quiroz-Flores, J. C. & García-López, Y. J. (2023). Improving Demand Forecasting by Implementing Machine Learning in Poultry Production Company. International Journal of Engineering Trends and Technology, 71(2), 39-45. https://doi.org/10.14445/22315381/IJETT-V71I2P205 | es_PE |
dc.identifier.issn | 2349-0918 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12724/17993 | |
dc.description | Indexado en Scopus | es_PE |
dc.description.abstract | The use of manual methods to forecast demand in perishable food companies is generally subject to the variability of internal and external factors in the company, causing excess inventories and significant monetary losses, so it is relevant to carry out this research with the objective of to demonstrate that by implementing Machine Learning it is possible to improve the accuracy of the demand forecast. A case study in a company in the poultry sector in Peru, forecasting the last quarter of 2022, based on a real sales database and applying the time series method, comparing the results of the Machine Learning model, and obtaining as a result in a model with high Forecast Accuracy (FA) of 97.56% and a high Forecast Bias (FB) of 2.44%. The research is an important contribution to knowledge, demonstrating that Machine Learning is an ideal tool to project the demand for perishable food products, ideal for its application in various fields, such as loss reduction control, preventive maintenance of machines and control of supplies such as water and energy, among others. | es_PE |
dc.format | application/pdf | es_PE |
dc.language.iso | eng | es_PE |
dc.publisher | Seventh Sense Research Group | es_PE |
dc.relation.ispartof | urn:issn: 2349-0918 | |
dc.rights | info:eu-repo/semantics/openAccess | es_PE |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.source | Repositorio Institucional - Ulima | es_PE |
dc.source | Universidad de Lima | es_PE |
dc.subject | Pendiente | es_PE |
dc.title | Improving Demand Forecasting by Implementing Machine Learning in Poultry Production Company | es_PE |
dc.type | info:eu-repo/semantics/article | es_PE |
dc.type.other | Artículo en Scopus | es_PE |
dc.identifier.journal | International Journal of Engineering Trends and Technology | es_PE |
dc.publisher.country | IN | es_PE |
dc.description.peer-review | Revisión por pares | es_PE |
dc.subject.ocde | https://purl.org/pe-repo/ocde/ford#2.11.04 | es_PE |
dc.identifier.doi | https://doi.org/10.14445/22315381/IJETT-V71I2P205 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_PE |
dc.contributor.student | Huertas Zúñiga, Sandra Larissa (Ingeniería Industrial) | |
dc.contributor.student | Garcia Arismendiz, Joaquin Antonio (Ingeniería Industrial) | es_PE |
ulima.autor.afiliacion | Lizárraga Portugal, Carlos Augusto (Facultad de Ingeniería y Arquitectura, Universidad de Lima) | es_PE |
ulima.autor.afiliacion | Quiroz Flores, Juan Carlos (Facultad de Ingeniería y Arquitectura, Universidad de Lima) | es_PE |
ulima.autor.afiliacion | García López, Yván Jesús (Facultad de Ingeniería y Arquitectura, Universidad de Lima) | es_PE |
ulima.autor.carrera | Lizárraga Portugal, Carlos Augusto (Ingeniería Industrial) | es_PE |
ulima.autor.carrera | Quiroz Flores, Juan Carlos (Ingeniería Industrial) | es_PE |
ulima.autor.carrera | García López, Yván Jesús (Ingeniería Industrial) | es_PE |
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