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Comparison of time series forecasting methods using neural networks and Box-Jenkins model.

The performance of the Box-Jenkins methods is compared with that of the neural networks in forecasting time series. Five time series of different complexities are built using back propagation neural networks were compared with the standard Box-Jenkins model. It is found that for time series with sea...

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Main Author: Shabri, Ani
Format: Article
Language:English
Published: Department of Mathematics, Faculty of Science 2001
Subjects:
QA Mathematics
Online Access:http://eprints.utm.my/id/eprint/8817/1/AniShabri2001_ComparisonOfTimeSeriesForecastingMethods.pdf
http://eprints.utm.my/id/eprint/8817/
http://www.fs.utm.my/matematika/content/view/50/31/
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id my.utm.8817
record_format eprints
spelling my.utm.88172010-08-13T02:56:37Z http://eprints.utm.my/id/eprint/8817/ Comparison of time series forecasting methods using neural networks and Box-Jenkins model. Shabri, Ani QA Mathematics The performance of the Box-Jenkins methods is compared with that of the neural networks in forecasting time series. Five time series of different complexities are built using back propagation neural networks were compared with the standard Box-Jenkins model. It is found that for time series with seasonal pattern, both methods produced comparable results. However, for series with irregular pattern, the Box-Jenkins outperformed the neural networks model. Results also show that neural networks are robust, provide good long-term forecasting, and represent a promising alternative method for forecasting. Department of Mathematics, Faculty of Science 2001-06 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/8817/1/AniShabri2001_ComparisonOfTimeSeriesForecastingMethods.pdf Shabri, Ani (2001) Comparison of time series forecasting methods using neural networks and Box-Jenkins model. Matematika, 17 (1). pp. 1-6. ISSN 0127-8274 http://www.fs.utm.my/matematika/content/view/50/31/
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic QA Mathematics
spellingShingle QA Mathematics
Shabri, Ani
Comparison of time series forecasting methods using neural networks and Box-Jenkins model.
description The performance of the Box-Jenkins methods is compared with that of the neural networks in forecasting time series. Five time series of different complexities are built using back propagation neural networks were compared with the standard Box-Jenkins model. It is found that for time series with seasonal pattern, both methods produced comparable results. However, for series with irregular pattern, the Box-Jenkins outperformed the neural networks model. Results also show that neural networks are robust, provide good long-term forecasting, and represent a promising alternative method for forecasting.
format Article
author Shabri, Ani
author_facet Shabri, Ani
author_sort Shabri, Ani
title Comparison of time series forecasting methods using neural networks and Box-Jenkins model.
title_short Comparison of time series forecasting methods using neural networks and Box-Jenkins model.
title_full Comparison of time series forecasting methods using neural networks and Box-Jenkins model.
title_fullStr Comparison of time series forecasting methods using neural networks and Box-Jenkins model.
title_full_unstemmed Comparison of time series forecasting methods using neural networks and Box-Jenkins model.
title_sort comparison of time series forecasting methods using neural networks and box-jenkins model.
publisher Department of Mathematics, Faculty of Science
publishDate 2001
url http://eprints.utm.my/id/eprint/8817/1/AniShabri2001_ComparisonOfTimeSeriesForecastingMethods.pdf
http://eprints.utm.my/id/eprint/8817/
http://www.fs.utm.my/matematika/content/view/50/31/
_version_ 1643645077811101696
score 13.211869

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