Independent Component Ordering in Time Series Forecasting
Gang Wang, HU De-wen · Journal of National University of Defense Technology · 2005
The ordering of independent components is a hot issue in independent component analysis(ICA),and the critical step for the robustness and computing complexity of independent feature space.In time series forecasting,a novel criterion has been presented based on the mechanism of first-order differential and minimum variance error under multiple components reconstruction.To avoid the exhaustive search in combinatorial optimization,a sub-optimum approach named Adding-Testing-Acceptance(ATA) is proposed.Experimental results show that the proposed method has a better forecasting ability and more efficient in comparison with the existing ones.