A hybrid GMDH and least squares support vector machines in time series forecasting
Time series consists of complex nonlinear and chaotic patterns that are difficult to forecast. This paper proposes a novel hybrid forecasting model which combines the group method of data handling (GMDH) and the least squares support vector machine (LSSVM), known as GLSSVM. The GMDH is used to deter...
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主要な著者: | Samsudin, Ruhaidah, Saad, Puteh, Shabri, Ani |
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フォーマット: | 論文 |
出版事項: |
Institute of Computer Science
2011
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主題: | |
オンライン・アクセス: | http://eprints.utm.my/id/eprint/28595/ http://dx.doi.org/10.14311/NNW.2011.21.015 |
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