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A Forecasting Model to Predict the Demand of Roses in an Ecuadorian Small Business Under Uncertain Scenarios

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A Forecasting Model to Predict the Demand of Roses in an Ecuadorian Small Business Under Uncertain Scenarios

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Herrera-Granda, ID.; Lorente-Leyva, LL.; Peluffo-Ordóñez, DH.; Alemany Díaz, MDM. (2021). A Forecasting Model to Predict the Demand of Roses in an Ecuadorian Small Business Under Uncertain Scenarios. Lecture Notes in Computer Science. 12566:245-258. https://doi.org/10.1007/978-3-030-64580-9_21

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/172310

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Title: A Forecasting Model to Predict the Demand of Roses in an Ecuadorian Small Business Under Uncertain Scenarios
Author: Herrera-Granda, Israel D. Lorente-Leyva, Leandro L. Peluffo-Ordóñez, Diego H. Alemany Díaz, María Del Mar
UPV Unit: Universitat Politècnica de València. Departamento de Organización de Empresas - Departament d'Organització d'Empreses
Issued date:
Abstract:
[EN] Ecuador is worldwide considered as one of the main natural flower producers and exporters ¿being roses the most salient ones. Such a fact has naturally led the emergence of small and medium sized companies devoted to ...[+]
Subjects: Bayesian-Networks-based forecasting , Demand forecast , Floriculture sector , Neural-Networks-based forecasting
Copyrigths: Reserva de todos los derechos
Source:
Lecture Notes in Computer Science. (issn: 0302-9743 )
DOI: 10.1007/978-3-030-64580-9_21
Publisher:
Springer-Verlag
Publisher version: https://doi.org/10.1007/978-3-030-64580-9_21
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
Project ID:
info:eu-repo/grantAgreement/EC/H2020/691249/EU/Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems/
Thanks:
Authors of this publication acknowledge the contribution of the Project 691249, RUC-APS ¿Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems¿ ...[+]
Type: Artículo Comunicación en congreso Capítulo de libro

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