2022
DOI: 10.23913/ride.v12i24.1203
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Análisis comparativo de modelos tradicionales y modernos para pronóstico de la demanda: enfoques y características

Abstract: En estadística inferencial, el pronóstico es un proceso matemático mediante el cual se hace una estimación del valor futuro de una o más variables, como puede ser la demanda. El objetivo de este presente trabajo de investigación documental fue definir la clasificación de los principales tipos de pronósticos. Además, proponer algunos de los modelos más representativos utilizados actualmente para ser implementados por pequeñas y medianas empresas, aquellos que, con base en la literatura consultada, tienen mayor … Show more

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“…Demand estimation through machine learning models or forecasting techniques based on quantitative and qualitative historical information [19]. The research work called "Comparative analysis of traditional and modern models for demand forecasting" [20] performs an analysis of demand forecasting methods through time series analysis, concluding that; "There is no forecasting model that can perfectly determine future demand," exposing the situation in which applying several methods for a future forecast in a given time, it will not be known which is the best until the result is at any given moment. The work exposes that the precision of the prediction will depend on the quantity, the quality, and the particular behavior of the time series data.…”
Section: Related Workmentioning
confidence: 99%
“…Demand estimation through machine learning models or forecasting techniques based on quantitative and qualitative historical information [19]. The research work called "Comparative analysis of traditional and modern models for demand forecasting" [20] performs an analysis of demand forecasting methods through time series analysis, concluding that; "There is no forecasting model that can perfectly determine future demand," exposing the situation in which applying several methods for a future forecast in a given time, it will not be known which is the best until the result is at any given moment. The work exposes that the precision of the prediction will depend on the quantity, the quality, and the particular behavior of the time series data.…”
Section: Related Workmentioning
confidence: 99%