A Comparison between Neural Networks and Traditional Forecasting Methods: A Case Study

Forecasting accuracy drives the performance of inventory management. This study is to investigate and compare different forecasting methods like Moving Average (MA) and Autoregressive Integrated Moving Average (ARIMA) with Neural Networks (NN) models as Feed-forward NN and Nonlinear Autoregressive n...

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Bibliographic Details
Main Authors: C. A. Mitrea, C. K. M. Lee, Z. Wu
Format: Article
Language:English
Published: SAGE Publishing 2009-09-01
Series:International Journal of Engineering Business Management
Online Access:https://doi.org/10.5772/6777
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spelling doaj-761ba1f323ed4f70842c9d7f237ab3212021-04-02T13:56:35ZengSAGE PublishingInternational Journal of Engineering Business Management1847-97902009-09-01110.5772/6777A Comparison between Neural Networks and Traditional Forecasting Methods: A Case StudyC. A. MitreaC. K. M. LeeZ. WuForecasting accuracy drives the performance of inventory management. This study is to investigate and compare different forecasting methods like Moving Average (MA) and Autoregressive Integrated Moving Average (ARIMA) with Neural Networks (NN) models as Feed-forward NN and Nonlinear Autoregressive network with eXogenous inputs (NARX). Data used to forecast is acquired from inventory database of Panasonic Refrigeration Devices Company located in Singapore. Results have shown that forecasting with NN offers better performance in comparison with traditional methods.https://doi.org/10.5772/6777
collection DOAJ
language English
format Article
sources DOAJ
author C. A. Mitrea
C. K. M. Lee
Z. Wu
spellingShingle C. A. Mitrea
C. K. M. Lee
Z. Wu
A Comparison between Neural Networks and Traditional Forecasting Methods: A Case Study
International Journal of Engineering Business Management
author_facet C. A. Mitrea
C. K. M. Lee
Z. Wu
author_sort C. A. Mitrea
title A Comparison between Neural Networks and Traditional Forecasting Methods: A Case Study
title_short A Comparison between Neural Networks and Traditional Forecasting Methods: A Case Study
title_full A Comparison between Neural Networks and Traditional Forecasting Methods: A Case Study
title_fullStr A Comparison between Neural Networks and Traditional Forecasting Methods: A Case Study
title_full_unstemmed A Comparison between Neural Networks and Traditional Forecasting Methods: A Case Study
title_sort comparison between neural networks and traditional forecasting methods: a case study
publisher SAGE Publishing
series International Journal of Engineering Business Management
issn 1847-9790
publishDate 2009-09-01
description Forecasting accuracy drives the performance of inventory management. This study is to investigate and compare different forecasting methods like Moving Average (MA) and Autoregressive Integrated Moving Average (ARIMA) with Neural Networks (NN) models as Feed-forward NN and Nonlinear Autoregressive network with eXogenous inputs (NARX). Data used to forecast is acquired from inventory database of Panasonic Refrigeration Devices Company located in Singapore. Results have shown that forecasting with NN offers better performance in comparison with traditional methods.
url https://doi.org/10.5772/6777
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