An Explainable Machine Learning Model to Optimize Demand Forecasting in Company DEOS

Gianella Cabrera Feijoo; Jimena  Germana Valverde; Yvan Jesus Garcia Lopez

An Explainable Machine Learning Model to Optimize Demand Forecasting in Company DEOS

Título traducido de la contribución: Un modelo explicable de machine learning para optimizar la previsión de la demanda en CompanyDEOS

Gianella Cabrera Feijoo, Jimena Germana Valverde, Yvan Jesus Garcia Lopez

Producción científica: Capítulo del libro/informe/acta de congreso › Articulo (Contribución a conferencia) › revisión exhaustiva

Resumen

Nowadays, having an accurate demand forecast is extremely important as it allows the company to manage resources in an optimal way and thus achieve greater productivity. There is a large demand for accurate forecasting, and utilizing artificial intelligence can help companies gain a better understanding of their market. In this research presentation, Machine Learning (ML) is used to optimize demand forecasting. The data collected was trained and due to the available data rate, the Cross-Validation technique was used to avoid overfitting. Using time-series, it will be possible to predict future sales for the first trimester of 2021. Finally, the impact of the ML tool on the deviation of the company's demand forecast was evaluated using indicators of accuracy (forecast accuracy) and bias (forecast bias).

Título traducido de la contribución	Un modelo explicable de machine learning para optimizar la previsión de la demanda en CompanyDEOS
Idioma original	Inglés
Título de la publicación alojada	ISSN / E-ISSN: 2169-8767: Proceedings of the International Conference on Industrial Engineering and Operations Management
Subtítulo de la publicación alojada	IEOM Society
Lugar de publicación	INDIA
Editorial	IEOM Society International
Páginas	1 - 12
Número de páginas	12
ISBN (versión digital)	978-1-7923-9160-6
ISBN (versión impresa)	2169-8767 (U.S. Library of Congress)
Estado	Publicada - 16 ago. 2022

Palabras Clave

Demand Forecast
Machine Learning
Forecast Accuracy
Forecast Bias and Consumers Good Company

COAR

Artículo

Categoría OCDE

Ingeniería industrial

Categorías Repositorio Ulima

Ingeniería industrial / Teoría

Temas Repositorio Ulima

Forcast
Demanda
Machine learning
Inteligencia artificial

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

Acceder al documento

http://ieomsociety.org/india2022/proceedings/

Citar esto

Cabrera Feijoo, G., Germana Valverde, J., & Garcia Lopez, Y. J. (2022). An Explainable Machine Learning Model to Optimize Demand Forecasting in Company DEOS. En ISSN / E-ISSN: 2169-8767: Proceedings of the International Conference on Industrial Engineering and Operations Management: IEOM Society (pp. 1 - 12). Artículo 490 IEOM Society International. http://ieomsociety.org/india2022/proceedings/

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Cabrera Feijoo, G, Germana Valverde, J & Garcia Lopez, YJ 2022, An Explainable Machine Learning Model to Optimize Demand Forecasting in Company DEOS. En ISSN / E-ISSN: 2169-8767: Proceedings of the International Conference on Industrial Engineering and Operations Management: IEOM Society., 490, IEOM Society International, INDIA, pp. 1 - 12. <http://ieomsociety.org/india2022/proceedings/>

An Explainable Machine Learning Model to Optimize Demand Forecasting in Company DEOS. / Cabrera Feijoo, Gianella; Germana Valverde, Jimena ; Garcia Lopez, Yvan Jesus.
ISSN / E-ISSN: 2169-8767: Proceedings of the International Conference on Industrial Engineering and Operations Management: IEOM Society. INDIA: IEOM Society International, 2022. p. 1 - 12 490.

Producción científica: Capítulo del libro/informe/acta de congreso › Articulo (Contribución a conferencia) › revisión exhaustiva

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