New product forecasting demand by using neural networks and similar product analysis

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Bibliographic Details
Main Author: Alfonso T. Sarmiento
Format: Artículo científico
Language:en
Published: Universidad Nacional de Colombia 2014
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author Alfonso T. Sarmiento
author_facet Alfonso T. Sarmiento
contents New product forecasting demand by using neural networks and similar product analysis Alfonso T. Sarmiento Osman Camilo Soto Ingeniería new products neural networks similar products demand forecasting This research presents a new product forecasting methodology that combines the forecast of analogous products. The quantitative part of the method uses an artificial neural network to calculate the forecast of each analogous product. These individual forecasts are combined using a qualitative approach based on a factor that measures the similarity between the analogous products and the new product. A case study of two major multinational companies in the food sector is presented to illustrate the methodology. Results from this study showed more accurate forecasts using the proposed approach in 86 percent of the cases analyzed. 2014 artículo científico 0012-7353 https://www.redalyc.org/articulo.oa?id=49631663039 en http://www.redalyc.org/revista.oa?id=496 Dyna application/pdf Universidad Nacional de Colombia Dyna (Colombia) Num.186 Vol.81
format Artículo científico
id redalyc_49631663039
institution Redalyc
language en
publishDate 2014
publisher Universidad Nacional de Colombia
spellingShingle New product forecasting demand by using neural networks and similar product analysis
Alfonso T. Sarmiento
Ingeniería
new products
neural networks
similar products
demand forecasting
New product forecasting demand by using neural networks and similar product analysis Alfonso T. Sarmiento Osman Camilo Soto Ingeniería new products neural networks similar products demand forecasting This research presents a new product forecasting methodology that combines the forecast of analogous products. The quantitative part of the method uses an artificial neural network to calculate the forecast of each analogous product. These individual forecasts are combined using a qualitative approach based on a factor that measures the similarity between the analogous products and the new product. A case study of two major multinational companies in the food sector is presented to illustrate the methodology. Results from this study showed more accurate forecasts using the proposed approach in 86 percent of the cases analyzed. 2014 artículo científico 0012-7353 https://www.redalyc.org/articulo.oa?id=49631663039 en http://www.redalyc.org/revista.oa?id=496 Dyna application/pdf Universidad Nacional de Colombia Dyna (Colombia) Num.186 Vol.81
title New product forecasting demand by using neural networks and similar product analysis
topic Ingeniería
new products
neural networks
similar products
demand forecasting
url https://www.redalyc.org/articulo.oa?id=49631663039