The application of an ensemble of boosted elman networks to time series prediction : a benchmark study

Lim, Chee Peng and Goh, Wei Yee 2006, The application of an ensemble of boosted elman networks to time series prediction : a benchmark study, International journal of computational intelligence, vol. 3, no. 2, pp. 119-126.

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Title The application of an ensemble of boosted elman networks to time series prediction : a benchmark study
Author(s) Lim, Chee Peng
Goh, Wei Yee
Journal name International journal of computational intelligence
Volume number 3
Issue number 2
Start page 119
End page 126
Total pages 8
Publisher World Academy of Science, Engineering and Technology
Place of publication Canakkale, Turkey
Publication date 2006
ISSN 1304-4508
1304-2386
Keyword(s) AdaBoost
Elman network
neural network ensemble
time series regression
Summary In this paper, the application of multiple Elman neural networks to time series data regression problems is studied. An ensemble of Elman networks is formed by boosting to enhance the performance of the individual networks. A modified version of the AdaBoost algorithm is employed to integrate the predictions from multiple networks. Two benchmark time series data sets, i.e., the Sunspot and Box-Jenkins gas furnace problems, are used to assess the effectiveness of the proposed system. The simulation results reveal that an ensemble of boosted Elman networks can achieve a higher degree of generalization as well as performance than that of the individual networks. The results are compared with those from other learning systems, and implications of the performance are discussed.
Language eng
Field of Research 109999 Technology not elsewhere classified
Socio Economic Objective 970110 Expanding Knowledge in Technology
HERDC Research category C1.1 Refereed article in a scholarly journal
Persistent URL http://hdl.handle.net/10536/DRO/DU:30048794

Document type: Journal Article
Collection: Centre for Intelligent Systems Research
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