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...
Main Authors: | , , |
---|---|
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 |
id |
doaj-761ba1f323ed4f70842c9d7f237ab321 |
---|---|
record_format |
Article |
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 |
work_keys_str_mv |
AT camitrea acomparisonbetweenneuralnetworksandtraditionalforecastingmethodsacasestudy AT ckmlee acomparisonbetweenneuralnetworksandtraditionalforecastingmethodsacasestudy AT zwu acomparisonbetweenneuralnetworksandtraditionalforecastingmethodsacasestudy AT camitrea comparisonbetweenneuralnetworksandtraditionalforecastingmethodsacasestudy AT ckmlee comparisonbetweenneuralnetworksandtraditionalforecastingmethodsacasestudy AT zwu comparisonbetweenneuralnetworksandtraditionalforecastingmethodsacasestudy |
_version_ |
1721563501084803072 |