Hybridization of nonlinear and linear models for time series forecasting
Nowadays, time series forecasting is very challenging due to the uncertainties of real world events that are influenced by many indefinite factors and rapid changes. This scenario requires forecasting methods that work efficiently with incomplete and multivariate data. Otherwise, the solutions will...
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| Format: | Thesis |
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2010.
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| Online Access: | Get fulltext |