Universiti Teknologi Malaysia Institutional Repository

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

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

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Official URL: http://www.fs.utm.my/matematika/content/view/50/31...

Abstract

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.

Item Type:Article
Uncontrolled Keywords:neural networks, back propagation, forecasting, robust
Subjects:Q Science > QA Mathematics
Divisions:Science
ID Code:8817
Deposited By: Ms Zalinda Shuratman
Deposited On:13 May 2009 04:20
Last Modified:13 Aug 2010 02:56

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