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
フォーマット: 論文
出版事項: Institute of Computer Science 2011
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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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