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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| Format: | Article |
| Language: | English |
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Department of Mathematics, Faculty of Science
2001
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| Online Access: | http://eprints.utm.my/8817/ http://eprints.utm.my/8817/1/AniShabri2001_ComparisonOfTimeSeriesForecastingMethods.pdf |
| _version_ | 1848891773282156544 |
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| author | Shabri, Ani |
| author_facet | Shabri, Ani |
| author_sort | Shabri, Ani |
| building | UTeM Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-15T21:03:17Z |
| format | Article |
| id | utm-8817 |
| institution | Universiti Teknologi Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T21:03:17Z |
| publishDate | 2001 |
| publisher | Department of Mathematics, Faculty of Science |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | utm-88172010-08-13T02:56:37Z http://eprints.utm.my/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/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/ |
| spellingShingle | QA Mathematics Shabri, Ani Comparison of time series forecasting methods using neural networks and Box-Jenkins model. |
| title | 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_short | 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. |
| topic | QA Mathematics |
| url | http://eprints.utm.my/8817/ http://eprints.utm.my/8817/ http://eprints.utm.my/8817/1/AniShabri2001_ComparisonOfTimeSeriesForecastingMethods.pdf |