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A Comparison of Machine Learning and Classical Demand Forecasting Methods: A Case Study of Ecuadorian Textile Industry

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A Comparison of Machine Learning and Classical Demand Forecasting Methods: A Case Study of Ecuadorian Textile Industry

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Lorente-Leyva, LL.; Alemany Díaz, MDM.; Peluffo-Ordóñez, DH.; Herrera-Granda, ID. (2021). A Comparison of Machine Learning and Classical Demand Forecasting Methods: A Case Study of Ecuadorian Textile Industry. Lecture Notes in Computer Science. 131-142. https://doi.org/10.1007/978-3-030-64580-9_11

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Title: A Comparison of Machine Learning and Classical Demand Forecasting Methods: A Case Study of Ecuadorian Textile Industry
Author: Lorente-Leyva, Leandro L. Alemany Díaz, María Del Mar Peluffo-Ordóñez, Diego H. Herrera-Granda, Israel D.
UPV Unit: Universitat Politècnica de València. Departamento de Organización de Empresas - Departament d'Organització d'Empreses
Issued date:
Abstract:
[EN] This document presents a comparison of demand forecasting methods, with the aim of improving demand forecasting and with it, the production planning system of Ecuadorian textile industry. These industries present ...[+]
Subjects: Demand forecasting methods , Textile industry , Machine learning , Classical methods , Forecast error
Copyrigths: Reserva de todos los derechos
Source:
Lecture Notes in Computer Science. (issn: 0302-9743 )
DOI: 10.1007/978-3-030-64580-9_11
Publisher:
Springer-Verlag
Publisher version: https://doi.org/10.1007/978-3-030-64580-9_11
Conference name: 6th International Conference on Machine Learning, Optimization, and Data Science (LOD 2020)
Conference place: Siena, Italy
Conference date: Julio 19-23,2020
Series: Lecture Notes in Computer Science
Thanks:
The authors are greatly grateful by the support given by the SDAS Research Group (https://sdas-group.com/).
Type: Artículo Comunicación en congreso Capítulo de libro

References

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